ENGINEERING RESEARCH PAPERS

image retrieval IEEE PAPER 2016




Comparative Analysis of Content Based Image Retrieval using Texture Features for Plant Leaf Diseases
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Abstract This research paper is an attempt to present comparative analysis of Content Based Image Retrieval (CBIR) using various texture features. CBIR system is developed for retrieving diseased leaf images of soybean. Performance of traditional texture features like Abstract. The content-based retrieval of diffusion magnetic resonance (dMR) imaging data would enable a wide range of analyses on large databases with dMR images. This paper proposes a content-based retrieval framework for dMR images to explore the use of

Image Retrieval Based on its Contents Using Features Extraction
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Abstract-With the increase in popularity of the network and development of multimedia technologies, users are not satisfied with the traditional information retrieval techniques so there should be an appropriate system to efficiently manage these collections. Due to the

Comparison of Image Retrieval Techniques Using Wavelets and Basic Features
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Abstract: To retrieve query image or sub regions of image, visual techniques are used such as color, shape, texture etc. Relevance feedback is used many times to improve the result and to help the user to express their preference. New approach is proposed in this paper

A Review on Histogram Value and Texture Descriptor Analysis for Image Retrieval
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Abstract Color and texture data have been the primitive image or picture descriptors in substance or content based picture recovery frameworks. In this article, a technique is introduced for image or picture mining taking into account examination of shading or color

Plant Disease Identification using Content Based Image Retrieval Techniques Based on Android System
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Abstract: Mobile phones are widely used devices around. Android, Windows Mobile, and the iPhone, mobile phones are different brands which have changed the way we look at mobile computing. Many applications like games, social networking, and bank transactions are

Content Based Image Retrieval Using Dominant Color and Texture Features
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The purpose of this Paper is to describe our research on different feature extraction and matching techniques in designing a Content Based Image Retrieval (CBIR) system. Due to the enormous increase in image database sizes, as well as its vast deployment in various

The Research of Image Retrieval based on Multi Feature DS Evidence Theory Fusion
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Abstract The traditional image retrieval method is based on single feature retrieval method like color, texture, shape or multi feature weighted fusion method. The retrieval rate of existing methods is not high. This paper presents fusion multi feature image retrieval. Two

Content Based Image Retrieval System over Hadoop Using MapReduce
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ABSTRACT A huge amount of image data is generated everyday due to rapid evolution of image capturing devices. Information associated to images has got diversified applications. The medical imaging systems produce more and more digitized images in all medical

Content-based Image Retrieval based on Integrating Region segmentation and colour histogram
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Abstract: Developments in multimedia technology, increasing number of image retrieval functions and capabilities has led to the rapid growth of CBIR techniques. Colour histogram could be compared in terms of speed and efficiency. We have presented a modified

Deep Quantization Network for Efficient Image Retrieval
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Abstract Hashing has been widely applied to approximate nearest neighbor search for large- scale multimedia retrieval. Supervised hashing improves the quality of hash coding by exploiting the semantic similarity on data pairs and has received increasing attention

Improved Accuracy of Image Retrieval by Using K-CBIR
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Abstract-The community networking sites like Facebook as well as Flicker allow users to upload the images. E-commerce web sites like flipkart and amazon etc. also provide number of products related images to user. Images which are present in social networking

A Content Based Image Information Retrieval for Medical MRI Brain Images based on Hadoop and Lucene (LIRe)
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Abstract: CBIR technique is one of the important techniques for feature extraction in medical field in order to store, manage, and retrieve image data based on user query. Searching is done by means of matching the image features such as texture, shape, or different

Content Based Image Retrieval Scheme using Color, Texture and Shape Features
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Abstract A novel approach of Content Based Image Retrieval (CBIR), which combines color, texture and shape descriptors to represent the features of the image, is discussed in this paper. The proposed scheme is based on three noticeable algorithms: color distribution

A Review Paper on Content Based Image Retrieval
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ABSTRACT Content Based Image Retrieval (CBIR) plays very important role in the research field of digital Image processing. DIP deals with manipulation of digital images through a digital computer. Basically CBIR is responsible for extracting low level features of image

Content-based image retrieval system for solid waste bin level detection
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47 Content-based image retrieval (CBIR) system is a process aims 48 to search image databases for specific images that are similar to 49 a given query image. The distance calculation between two image 50 codes with equal length is the most common method

A Novel Modified Evolutionary Algorithm based Image Retrieval Framework: Theoretical Analysis and Applications
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Abstract With the fast development of data analysis and computer science technology, the design and implementation of image retrieval system has been a hot topic. The prior research focus more on image-size based approaches which are not intelligent or

Image Object Retrieval Using Distribution of Mixed Shape Descriptors
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Abstract: Most of the real world objects are characterized by their shape. Computing the shape signature to truly reflect the object of interest is proceeded through the edge detection, extraction of relevant features from the border pixels. In this paper, we propose

A DISTRIBUTIONAL APPROACH FOR IMAGE RETRIEVAL USING HOTELLING'S T-SQUARE STATISTIC
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Abstract This paper proposes a novel method, based on a statistical probability distributional approach, Hotelling's T2 statistic and Orthogonality test. If the input query image is structured, it is segmented into various regions according to its nature and structure.

A Survey on Image retrieval techniques with feature extraction
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Abstract-In the past researches, Image retrieval was the part of searching trends in research and development. The reason behind those trends is additional need of multimedia and text data on internet. As the content based image retrieval techniques outperforms because of

Content Based Image Retrieval using Combination of Wavelet Transform and Color Histogram
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Abstract:As collections of images are increasing at a rapid rate, demand for effective tools for retrieval of query images from large image databases has increased in significant manner. Among them, content-based image retrieval systems (CBIR) are very popular as

Image Retrieval Based on Deep Belief Networks
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Abstract According to the local and global feature of image, matching the image from a lot image library, this is the image retrieval task; however, the image retrieval need to search the information in the database, we need to find a method for efficient information retrieval.

Content Based Image Retrieval: A Study
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Abstract: Content Based Image Retrieval (CBIR) is the today's most active area in information retrieval and image processing. An image contain various visual information that is difficult to extract manually, the CBIR system aims at finding the most appropriate image

Archival and Retrieval of Lost Objects using Multi-feature Image Matching in Mobile Applications
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Abstract: The rapid development of mobile computing technologies, as well as enhanced wireless communications, has paved the way for the development of the e-Government and m-Government systems. With the aim of increasing the accessibility of government

Research on New Multi-Feature Large-Scale Image Retrieval Algorithm based on Semantic Parsing and Modified Kernel Clustering Method
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Abstract Because of the feature points can describe the local characteristics of the image in a reasonable manner, effective use of feature point of content based image retrieval become the current hot issues in the field of computer vision. Aiming at this problem, we put

A New Histogram Based Shape Descriptor in Image Retrieval
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Abstract A shape based descriptor in image retrieval is proposed in this paper. It is focused on developing soft computing efficiency and novelty in image processing. The algorithm calculates a histogram based on the shape descriptor, representing texture feature of an

Scalable Face Image Retrieval Using Attribute Patch Reinforcement and Sparse Coding
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Abstract: In today's life variety applications including face identification and also use face image retrieval method. This technique is quite challenging since all the faces will appear similar at initial level due to similar geometry of face structure configuration. This paper

A Study Paper on Required Image Retrieval by Capturing User Intention UsingImage Pool Clustering
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Abstract:Web-scale image search engines (eg, Google image search, Bing image search) mostly rely on surrounding text features. It is hard for them to interpret users' search intention only by query keywords and this leads to ambiguous and noisy search results which are

An Effective Technique for the Content based Image Retrieval to Reduce the Semantic Gap based on an Optimal Classifier Technique
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ABSTRACT: Content Based Image Retrieval (CBIR) systems use Relevance Feedback (RF) in order to improve the retrieval accuracy. Research focus has been shifted from designing sophisticated low-level feature extraction algorithms to reducing the 'semantic gap'

A Study on Image Retrieval Techniques Based On Visual Features
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Abstract-The image retrieval is fascinating and quickest developing methodology altogether fields. Recently, the content-based image retrieval has become the recent topic and therefore the techniques of content-based image retrieval (CBIR) are achieved nice

Semantic-Based Web Mining For Image Retrieval Using Enhanced Support Vector Machine
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Abstract This paper deals with the semantic-based web mining for image retrieval by means of enhanced Support Vector Machine (SVM). Generally, conventional Content-Based Image Retrieval (CBIR) systems are unsuccessful to satisfy users' requirement because of the '

Geometrical Coding For Medical Image Retrieval Using Transformed Contour Coding
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Abstract In the approach of geometrical coding, curvature based coding are predominantly been used. As in various applications the processing data are large in count or large in representation and the available resources are very lower in count. In such resource

Content Based Image Retrieval using color
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Abstract Content-based Image Retrieval (CBIR) technology overcomes the defects of traditional text-based image retrieval technology, such as heavy workload and strong subjectivity. It makes full use of image content features (color, texture, shape, etc.), which

Automatic Image Annotation and Retrieval: A Survey
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Abstract-Image Annotation and Retrieval (IR) is one of the most exciting and fastest growing research areas in the field of multimedia technology. Manual image annotation is time- consuming, laborious and expensive. Automatic Image annotation and retrieval is a

3D Shape Retrieval Using a Single Depth Image from Low-cost Sensors
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Abstract Content-based 3D shape retrieval is an important problem in computer vision. Traditional retrieval interfaces require a 2D sketch or a manually designed 3D model as the query, which is difficult to specify and thus not practical in real applications. With the recent

A Review of Feature Extraction Methods in Content Based Image Retrieval
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Abstract: Image retrieval is an active research area for the last two decades. This area is gaining more importance as the growth of multimedia content over the internet is increasing. Content Based Image Retrieval (CBIR) uses the visual content of images like color, shape

An Enhanced Technique for Image Retrieval Using Texture Features
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Abstract---Content-Based Image Retrieval (CBIR) uses the visual contents of an image such as color, shape, texture and spatial layout to represent and index the image. The CBIR is the process of retrieving images from a database or library of digital images according to the

Feature Fusion of Colour Moment and Morphological Features for Enhanced Precision in Content Based Image Retrieval Systems
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Abstract In this paper we propose an algorithm that learns to combine the distance measure using different feature sets in appropriate weights. The distance measure is the measure of all the images in the data set to the query image. This combined distance is them used for

Improving Content based Image Retrieval System Using SIFT and SVM
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Abstract-The current improvement in the digital storage media, image capturing devices like scanners, web cameras, digital cameras and rapid development in internet provide a huge collection of images. This leads to the retrieval of these images for visual information

Click through Image Retrieval Based 0n Index Codes
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Abstract: Web image search is the major aspect in present days like Google image search. It is difficult for them to interpret users' search intention only by query keywords and this leads to ambiguous and noisy search results which are far from satisfactory. For producing these

Neutrosophic Image Retrieval with Hesitancy Degree
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Abstract The aim of this paper is to present texture features for images embedded in the neutrosophic domain with Hesitancy degree. Hesitancy degree is the fourth component of Neutrosophic set. The goal is to extract a set of features to represent the content of each

PERFORMANCE EVALUATION OF PROPOSED IMAGE RETRIEVAL SYSTEM FOR IMAGE-RICH INFORMATION NETWORKS BASED ON INTEGRATED
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Abstract:Due to existence of different related information to images (tags, annotations, comments etc.) retrieval of images from image rich information networks is very challenging and complex task. Integrated algorithm (SCBIR) issued to retrieve images from image rich

Object Recognition Using DRLBP for Image Retrieval Systems
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Abstract: The project presents the robust object recognition using edge and texture feature extraction. The system proposes new approach in extension with local binary pattern called DRLBP. By using these methods, the category recognition system will be developed for

Partial Image Retrieval Systems in Luminance and Color Invariants: An Empirical Study
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Abstract-Color of the surface is one of the most imperative characteristics in the process of recognition as well as classification of the object which is based on camera. On the other hand, color of the object sometimes differs a lot due to the difference in illumination as well

Powerful Combination of Color Descriptor and LBP Descriptor for Image Retrieval
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Abstract: The search for visual information in large mass of multimedia data has become essential with the digital evolution. This sparked a need for development of information search techniques by visual content; the performance of such a search system depends

STUDY BASED PERFORMANCE ANALYSIS OF CONTENT BASED IMAGE RETRIEVAL TECHNIQUES BASED ON VISUAL FEATURES
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ABSTRACT The area of multimedia contents increases online day by day. Therefore image data availability search has become a feasible way of retrieving relevant images. Content- Based Image Retrieval has emerged as an important area in computer vision and

Literature Survey on Latest trends in Content Based Image Retrieval (CBIR) Applications by Indian Authors in year 2015
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Abstract The Content Based Image retrieval (CBIR) is up-and-coming exploring area that deals with image retrieval using visual feature extraction, multidimensional indexing, and retrieval system design. Literature survey is most important for understanding and gaining

Neutrosophic Features for Image Retrieval
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Abstract The goal of an Image Retrieval System is to retrieve images that are relevant to the user's request from a large image collection. In this paper we present texture features for images embedded in the neutrosophic domain. The aim is to extract a set of features to

Visual Cryptography Scheme for Secret Image Retrieval
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ABSTRACT: In multimedia system, first the message will encrypt and then it will hide into an image file. So that we can use Cryptography because this can converts the message into an unreadable text. These both provide the security over the unsecured communication

K-MED: An Algorithm of Uniform Clustering for Efficient Content-Based Image Retrieval
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ABSTRACT Currently, search and retrieval of the relevant images efficiently from the huge amount of data is a challenging task for the researchers. Clustering is much useful in image segmentation to segregate a digital image into discrete regions that can be used to

IMAGE RETRIEVAL USING BIASED DISCRIMINANT EUCLIDEAN EMBEDDING WITH RELEVANCE FEEDBACK
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ABSTRACT With many potential multimedia applications, content-based image retrieval (CBIR) has recently gained more attention for image management and web search. A wide variety of relevance feedback (RF) algorithms have been developed in recent years to

A Review on Content-Based Image Retrieval System Using Halftoning BBTC
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Abstract-The Image Retrieval system is implementing antecedently on varied parameters likewise an image retrieval system returns a collection of images from a set of images within the information to fulfill user's demand with image content similarity, edge pattern similarity

Sketch Based Image Retrieval
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Abstract Sketch based image retrieval is a task that has been explored a lot recently as an alternative method for image retrieval. We develop this task on The Sketchy Database, where we use Siamese and Triplet network to perform sketch based image retrieval. We

Comparative study of image retrieval methods for mining user queries
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Abstract:Image retrieval is most important concept nowadays. When user provides a query in the form of keywords or in the form of image then system provides similar kind of images according to user queries. When database is very large then to deal with such database is

Understanding the Fundamentals of Content Based Image Retrieval System
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Abstract: Image retrieval system is used for browsing, searching and retrieving images from a large database of digital images. Content-based means that the search analyzes the contents of the image rather than the metadata such as keywords, tags, or descriptions

Survey on Sketch Based Image Retrieval
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Abstract: Sketch-based communication is the oldest form of writing. In which sketch depicts rough shape of object. Sketch-based image retrieval (SBIR) can therefore be a very valuable information search tool. Although sketch is good way to express people's thoughts, there

Content Based Image Retrieval using Color, Multi-Dimensional Texture and Edge Orientation
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Abstract Many image retrieval systems use global features to retrieve images such as color and texture. But the previous results provide too many false positives while using these global features to search for similar images. Content-based image retrieval system works

Comparison between Local Binary Pattern and Chain Code Techniques forImage Retrieval using Sketches
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Abstract: The paper compares two Sketch Based Image Retrieval schemes used for the image retrievals. The various schemes for image retrieval are Local Binary Patterns (LBP), and Chain Code. In Local Binary Patterns (LBP), it describes the neighborhood of a pixel

Active Learning Method for Interactive Image Retrieval
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Abstract:With many possible multimedia applications, content-based image retrieval (CBIR) has recently gained more interest for image management and web search. CBIR is a technique that utilizes the visual content of an image, to search for similar images in large-

Image Retrieval for Improved Law and Order
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1 Page 2. ImageRetrieval for Improved Law and Order Search, Analyse, Predict Image Spread on Twitter cerc.iiitd.ac.in Current State of Art Content based imageretrieval (CBIR) Colour, texture, size, shape: A combination of color and shape is a more robust feature than

SURVEY ON MULTI QUERY CONTENT BASED IMAGE RETRIEVAL SYSTEMS
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SURVEY ON MULTI QUERY CONTENT BASED IMAGERETRIEVAL SYSTEMS betty.p.cse@kct.ac.in ABSTRACT Keywords: Content based imageretrieval (CBIR), Feature matching, Multiple query imageretrieval (MQIR), semantic gap reduction techniques. 1 Introduction

A Novel Iris Image Retrieval with Boundary Based Feature Using Manhattan Distance Classifier
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Abstract:Image processing enters into various sectors but still it is struggling in recognition issues. Iris recognition developed into a very significant research area concentrate on how to extract and recognize iris images. Iris recognition is an extensively used biometric

Segmentation and Feature Extraction of Flowers Intended for Image Retrieval: A survey
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Abstract:Flower image retrieval is a very important step for computer-aided plant species identification. The paper elaborates the segmentation technique and feature extraction schema proposed by different authors. Firstly the flower area is extracted from the

Content Based Image Retrieval Using Enhanced Vocabulary
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Abstract: Content Based Image Retrieval is a technique that makes use of the visual content of an picture, to search for similar pictures in large-scale image databases, as per a user's interest. The CBIR is driven by the requirement to go looking the exponentially increasing

An Enhanced Technique for Image Indexing and Retrieval with Orientation Features Using Autocorrelation Function
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Abstract--In this paper, the rectangular features of an image are considered for generation of feature set and compared with the existing techniques. The orientation features are extracted for the establishment of feature set for image indexing and retrieval. The

Similarity Measurement using Shape Feature for Image Retrieval
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ABSTRACT In this paper, we describe a method on contour and shape feature, by using this method, the category recognition system will be developed for image retrieval. The category recognition is to classify an object into one of several predefined categories. These

A Review on Image Retrieval Techniques
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Abstract---Rapid and explosive growth of digital libraries due to the invention of Web cameras, digital cameras, and mobile phones equipped with such devices is making the database management by human annotation an extremely tedious and clumsy task.

DEEP IMAGE RETRIEVAL AND CLASSIFICATION ON SPARKNET
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ABSTRACT Image retrieval and classification are hot topics in computer vision and have attracted great attention nowadays with the emergence of large-scale data. We propose a new scheme to use both deep learning models and large-scale computing platform and

Augmented Performance Analysis of Block Truncation Coding based Image Retrieval techniques through sundry similarity measures
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Abstract: Block Truncation Coding based image retrieval techniques are one of the prominent techniques that are widely used for content based image retrieval (CBIR) systems. It gives better efficiency and accuracy for CBIR system, due to which it is possible

Rank Based Image Retrieval Technique using Hue Saturation and Value (HSV) and Gray Level Co-occurrence Matrix (GLCM) Features
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Abstract: Content based image retrieval is an effective approach to retrieve most similar images to the query from a large set of database. various contents are used as color, tecture, shape, sketch. In this work only color and texture are used with the extraction of HSV (Hue,

IMAGE RETRIEVAL USING CLUSTER BASED APPROACH
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Abstract-This paper addresses the issue of effective and efficient content based image retrieval by presenting a novel indexing and retrieval methodology that integrates color, texture, and shape information for the indexing and retrieval, and applies these features in

Sketch Based Image Retrieval System
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Abstract: The systematic approach that bridges the appearance gap for Sketch Based Image Retrieval System. The existence of noisy edge on photo realistic images is factor in enlargement of appearance gap and significantly degrades performance. To bridge this

Deep Supervised Hashing for Fast Image Retrieval
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Abstract In this paper, we present a new hashing method to learn compact binary codes for highly efficient image retrieval on large-scale datasets. While the complex image appearance variations still pose a great challenge to reliable retrieval, in light of the recent

Content based Image Retrieval using Model Approach
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ABSTRACT Due to rapid development of digital and information technologies, more multimedia information is generated and available in digital form from varieties of resources around the world. Content based image retrieval systems (CBIR) are designed to allow

A MEDICAL X-RAY IMAGE CLASSIFICATION AND RETRIEVAL SYSTEM
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Abstract Medical image retrieval systems have gained high interest in the scientific community due to the advances in medical imaging technologies. The semantic gap is one of the biggest challenges in retrieval from large medical databases. This paper presents a

Image Retrieval Algorithm Based on Figure Feature and SIFT Feature
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Abstract To the lower precision rate of image retrieval system, this paper presents a content- based image retrieval algorithm based on contour feature and SIFT (scale-invariant feature transform) feature. In our algorithm, firstly we use roughness and steering dangle to

Review of the Signature Matching Distance for Content-based Image Retrieval
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Zusammenfassung Beecks, Kirchhoff, and Seidl [4] introduced the Signature Matching Distance (SMD) and showed it to be a simple yet effective approach to content-based image retrieval. I have reviewed their paper and the related work and examined the SMD for

IMAGE RETRIEVAL BY USING HISTOGRAM EQUALIZATION AND CBIR
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Abstract-In this paper, we discuss some of the key contributions in the current decade related to image retrieval and automated image annotation. General content-based image retrieval (CBIR) also could be improved by the proposed approach in a similar manner as

IMAGE RETRIEVAL USING CONTENT-BASED
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Abstract--The last decade has witnessed great interest in research on content-based image retrieval. This has paved the way for a large number of new techniques and systems, and a growing interest in associated fields to support such systems. Likewise, digital imagery

Color, Shape and Texture feature extraction for Content Based Image RetrievalSystem: A Study
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Abstract: Content based image retrieval system is the most interested topic for researchers in these the three visual features are considered as color, shape and texture, these terms are refers as content in a content based image retrieval system. Although the visual features

A Content-Based Image Retrieval Semantic Modelfor Shaped and Unshaped Objects
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Abstract: This paper presents an efficient content based image retrieval scheme for both the shaped and unshaped objects. The local regions of an unshaped image have been classified with respect to the frequency of occurrence. Then the semantic concept is

Review on Content Based Image Retrieval: From Its Origin to the New Age
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Abstract: Content Based Image Retrieval (CBIR) is a process in which for a given query image, similar images will be retrieved from a large image database based on their content similarity. The content of image refer to its features or attributes or parameters which are

A Literature Survey of Image Descriptors in Content Based Image Retrieval
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Abstract-As a result of the new communication technologies and the massive use of Internet in the society, the amount of audio-visual information available in digital format is increasing considerably. This has necessitated designing systems that allow describing the content

A Review on Multi-Keyword Based Image Retrieval System for EncryptedImage Data Stored On Cloud
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Abstract-In recent years, cloud computing has become an advanced area, particularly due to its potential merits and applications. Also CBIR has become the active research topic in the area of computer science in past few years. In order to realize the cloud computing, many

Deep Semantic-Preserving and Ranking-Based Hashing for Image Retrieval
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Abstract Hashing techniques have been intensively investigated for large scale vision applications. Recent research has shown that leveraging supervised information can lead to high quality hashing. However, most existing supervised hashing methods only construct