image retrieval

Hierarchical image retrieval extracts the Gauss mixture parameters of image class from that of images by clustering algorithm.

Within the image retrieval based on the content, the color, being an important vision information of image, have been used broadly.

Experiment results from the database with 1000 general images show that this method is satisfactory for the image retrieval.

The radius histogram and angle histogram of each color blocks are used to compute the similarity of images for image retrieval.

This two-level semantic annotation research is of great significance to the semantic-based image retrieval system.

In the animation image retrieval system, image semantic annotation has a directly influence on the result of image retrieval.

Finally, base on the research of image retrieval at present, it discusses the develop direction of image retrieval technology.

Simulation results demonstrate that it can be used for the application of content based image retrieval.

For the lack of valuable prior knowledge in the image retrieval process, unsupervised clustering algorithms should be applied.

CBIR(Content-Based Image Retrieval) is a very important area of graph analyze and also the difficult of the search engine technology.

Absrtact: Active learning plays a vital role in image retrieval with a little amount of training instances.

The Content-Based Image Retrieval (CBIR) has become one of the hot research areas in image domain for large image database.

But the existence of a semantic gap is the major obstacle of image retrieval technology.

In Content-Based Image Retrieval (CBIR) area, features extraction and matching are the key technique for image retrieval.

Model, Implementation, and Experiments for Fine-Grained Image Retrieval. National Taiwan University, Taipei, Taiwan.

Image retrieval can take advantage of the desktop or Enterprise version of the search engines through the folder structure of the customer.

Content-based image retrieval work includes feature selection, object representation, and matching.

So this spatial relation descriptor will performance well in image recognition, image retrieval and image registration.

Summarizes the image retrieval development firstly, and then analyzes research status and the localization of shape- based image retrieval.

The color feature is chosen as the research emphasis and the key technology refer to color-based image retrieval is discussed.

AN IMPORTANT issue in the area of image retrieval is to determine how similar two images are to each another.

The experimental results indicate that the proposed method is feasible for design patent image retrieval.

Finally we design and develop several image context mining and image retrieval prototypes for different requirements.

Color space, color quantization and color feature extraction are the main techniques in image retrieval based on color feature.

Finally, in the image retrieval system, introduced correlation feedback to enhance the retrieval efficiency.

For aiming at image segmentation of design pattern image retrieval specially, this algorithm show good adaptability.

Color and shape are common features which were used in the Content Based Image Retrieval System.

Concerning about the characteristic of the cultural relic images, a new approach was proposed to cultural relic image retrieval.

The preparation of typical coating corrosion samples and common frame of grey histogram-based image retrieval are presented.

So, the system kernel of Content-based image retrieval is choose and distill the characteristicistic of image.

As known to all, content-based image retrieval is mainly stimulated under the combination of pattern recognition and multimedia database.

Image correspondence is a very hot topic for image panorama, remote sensing and image retrieval.

But only a method applies to image retrieval could not express attributes of image completely.

Image retrieval is an important research branch on multimedia retrieval.

Experimental results show that the new method is efficient and it provides noticeable improvement to the performance of image retrieval.

The main contents of this paper include color analysis, image segmentation, image database construction and image retrieval and so on.

The SIFT features of gray-scale image is extracted and applied to image retrieval, which is a hot topic at home and abroad.

Image emotion semantic classification is an important and challenging task in the field of semantic-based image retrieval.

Relevance feedback (RF) based on multiple instance learning (MIL) was applied to the remote sensing image retrieval.

An efficient method which based on the image classification is being used to the image retrieval .

The traditional float vector based image feature is the base of content based image retrieval techniques.

The paper adopts the method of the combination of GGD model and KL distance to get the image retrieval precision rate.

To conclude, some suggestions on image literacy and image retrieval system design were provided.

Last, an algorithm of image retrieval based shape feature directly in DCT compressed domain is proposed.

Aiming at the 72-dimensional HSV color feature in content-based image retrieval(CBIR), this paper proposes a new dimension reduction idea.

A novel content-based image retrieval method is proposed using information entropy in this paper.

The traditional image retrieval is unable to meet our need which is based on file name or the description of the image file.

Firstly, this paper presents the trademark image retrieval method based on distance distribution information entropy.

A novel content-based face image retrieval scheme is created based on this content feature-principle independent content feature (PICF).

A novel method for image retrieval based on color and spatial distribution features of interest points was presented.

Lastly, this paper presents the trademark image retrieval method based on region orientation information entropy.

Compared with direct use of gray histogram image retrieval, this algorithm possesses high distinguish degree.

Single feature-based image retrieval often catches one and loses another, so it can't integrate the advantages of each feature.

Because we can hardly get better performance using one feature of an image, we combined the color and texture features for image retrieval.

Secondly, this paper presents the trademark image retrieval method based on normalized unit moment of inertia features.

Firstly a user-oriented image retrieval framework is proposed.

An image retrieval method based on curvature feature and entropy-matrix feature for binary trademark images was proposed.

Conclusion A method of image retrieval using GA based self-learning is presented.

In traditional method of image retrieval searches images according to keys, number and sort describe from image database.

In recent years, the research of content based image retrieval is a focus.

Relevance feedback algorithm based on support vector machine and rough set for image retrieval is approached.

This search system has greatly enhanced the image retrieval accuracy 11. 8% than that of the single feature-based.

Finally it carries out image retrieval based on multi-feature by combining color component and shape component.

Through testing, we can see that these methods for content-based image retrieval have very good results.

The contents of image include low level visual features and high level semantic in image retrieval based on content.

image retrieval systems are mostly based on low-features, but people are accustomed to judging on high-semantic level.

This paper introduces a memory learning based image retrieval method by using the ant colony algorithm.

A fuzzy logic-based image retrieval system is proposed.

A novel remote sensing image retrieval method based on artificial immune system (AIS) is proposed in this paper.

Color histogram is an important method of image retrieval based on color feature.

An image retrieval method based on user selected region of interest was proposed.

This paper proposes an image retrieval method based on NMI (Normalized Monent of Inertia) invariable feature for binary trade mark images.

Content-Based Image Retrieval is a technique for retrieving images on the basis of image features such as colors, textures and shapes, etc.

Content-based image retrieval technology is the technology that can retrieval a lot of pictures from image databases.

Therefore, content-based image retrieval techniques have emerged, and it become hot in the field of image retrieval research.

This is an important step for data mining and content-based image retrieval (CBIR).

An image retrieval method for design patent is proposed based on multi-feature fusion.

In the end, we apply the object region extracted automatically into image retrieval based on object region.

That's because we can combine active learning with support vector machines to improve the accuracy of image retrieval.

A novel image retrieval method was proposed based on salient points and key blocks.

There are various applications of clustering analysis techniques in the field of image retrieval.

So the new method is valuable for texture image retrieval in the future.

It can get more user's potential requirements and improve search greatly by using self-learning process of GA in image retrieval.

Visualized Interactive Genetic Algorithm and its Application in Kansei-based Image Retrieval

Distance Distribution Histogram and its Application in Trademark Image Retrieval

Research and Implementation of a Content-based Image Retrieval Algorithm

The Design and Realization of a Content-based Remote Sensing Image Retrieval System

Wavelet Analysis and its Applications in Content-Based Image Retrieval Technology

Research and Implementation of a Content-Based Image Retrieval System

study of content - based image retrieval algorithm for necktie pattern

Research to the Application of Mutual Information and Improved Color Quantization Method in Content Based Image Retrieval

Memorization and Semi-Supervision Based Active Relevance Feedback Algorithm for Content-Based Image Retrieval

Design and Implementation of A Content-Based Image Retrieval System

Study on content- based image retrieval technology and its implementation

Complexity Histogram of Image and Its Application in Content-Based Image Retrieval

Implementation of A Content-based Image Retrieval System

Implementation of Cultural Heritage Image Retrieval and Research on Its Key Techniques

An Application of a Content-Based Medical Image Retrieval Method

The Methods and Applications of Pattern Classification and Image Retrieval by Color Characteristics

Content-based image retrieval and its application to water conservancy

A New Approach for Image Similarity Definition and Its Application to Image Retrieval

Comparison of Two Image Retrieval Methods Using Texture Features

Non-negative Matrix Factorization Based Relevance Feedback Algorithm in Image Retrieval

Color-based image retrieval technical research for the strip- steel facial quality's monitoring

Content-Based Image Retrieval using Texture Spectrum Histogram and Latent Semantic Indexing

Construction Method of a New Type Semantic Network for Image Retrieval

A Method and Implementation for Region-based Image Retrieval Using Partition of Foreground and Background

Research on the integer-to-integer wavelet-coefficient-based texture image retrieval techniques

Combined distance and correlation measurement for content-based image retrieval

Semantic Image Retrieval Technique Using Compressed-Domain Features

Development Research of Relevance Feedback in Interactive Image Retrieval

Content Based Image Retrieval Technology of Ultrasound Image Oriented Image Database

proposed a MIL bag generator which is suitable to image retrieval, and implemented it in a prototype system;

The results of research include: established a general framework for object-based image retrieval;

Principle of content-based image retrieval and prospects of microscopic identification of TCM

Regions with Tree Relationships Segmented on Shape Features Matching for Image Retrieval

The application of feature integration and relevance feedback in medical image retrieval

Research of a Vector Space-based Image Retrieval System

Application of Relevance Feedback Techniques in Content-Based Image Retrieval

A Novel Relevance Feedback Technique for Interactive Content-Based Image Retrieval

A Relevance Feedback-Based Image Retrieval with an Updatable Feature Database

Active Learning and Its Scalability for Image Retrieval

A Image Retrieval Model of Fractal-based Encoding Topological Characteristic

Support vector machine based relevance feedback algorithm in image retrieval

The user can gain the hot image retrieval result from the server end in the shorter response time with the memory cache;

Comparative Studies on Similarity Measures for Texture Image Retrieval

An Approach to Combining Dominant Color of Partition with Relevance Feedback in Image Retrieval

Constructing Distributed Image Retrieval System with CORBA

Similarity Measurement and Relevance Feedback in Image Retrieval

Content-based intellectually image retrieval in. NET environment

Application of content-based image retrieval for forest diseases and pests management

Relevance retrieval scheme of image features in content-based image retrieval systems

A Forward Neural Network Based Relevance Feedback Algorithm Design in Image Retrieval

Content-Based Interactive Emotional Image Retrieval

Feature Performance Evaluation in Content-Based Image Retrieval

Multiscale Relativity Algorithm for Shape-Based Image Retrieval

Application of Content-based Image Retrieval in Intelligent Monitor System

Active Learning with Labeled and Unlabeled Samples for Content-Based Image Retrieval

Spectral Similarity Measure Based on Set Theory and Its Application to Hyperspectral RS Image Retrieval

Application of Local Accumulation Histogram in Color Image Retrieval

Application of Content-Based Image Retrieval to Radar Scene Matching Image Database

Base on Content-based Image Retrieval Improved for the Feedback Algorithm

Color-based Feature Extraction and Matching Algorithms on Image Retrieval

Auto-expanded multi query examples technology in content-based image retrieval

Design of an Extensible Image Retrieval Platform

Relativity Feedback Mechanism of Content-based Image Retrieval

Multiresolution Histogram Based Image Retrieval with Pseudo-Multiple Examples

Content-based Image Retrieval Using Combination Features

Content-based image retrieval in database using SVM and gray primitive co-occurrence matrix

Wavelet Coefficients Generalized Gaussian Distribution Image Retrieval Algorithm Based on Shape

The research of image retrieval methods based on approaching the contour of a shape by ellipses

Content-based image retrieval technique and medical image retrieval

Technical Principles and Methods of Content - based Image Retrieval

Research on content-based image retrieval and video retrieval technology

Research for Texture Feature Extraction in Content-based Image Retrieval

The Combination of Relevance Feedback and Data Mining in Content-based Image Retrieval

Relevance Feedback Technique in Content-based Image Retrieval

Wavelet Multi-scale Features Clustering Based Image Retrieval

Research on Compressed Domain Image Retrieval Technique

Texture Spectrum Descriptor Based Image Retrieval

An image retrieval method using image information entropy and fractal vector

Research on Content-based Image Retrieval in Remote Sensing Imagery Database

Two-Level Description and Unbalanced Region Matching in Image Retrieval

The Application of Color Texture Shape and Relevance Feedback in Image Retrieval

Meaningful regions-based algorithm for color image retrieval

Research and Implementation of Content-based Image Retrieval

Content-Based Image Retrieval and Relevance Feedback issues in it

Research on wavelet based compression for image retrieval systems

An Improved Algorithm for Content Based Trademark Image Retrieval

Using clustering algorithm to enhance accuracy of image retrieval

A Novel Feature Descriptor Based Local Information for Image Retrieval

A Qualitative Approach to Content-based Image Retrieval with Histogram

Fractal Coding Based Image Retrieval Using Histogram of Collage Errors

An Overview of Performance Evaluation in Content-based Image Retrieval

A Relevance Feedback Method in Image Retrieval with Analyzing Feedback Log

A Survey of Relevance Feedback Techniques in Content-Based Image Retrieval

A Region Character-Based Image Retrieval and Implementation

research on the integer - to - integer wt - based color image retrieval method

Remote Sensing Image Retrieval Using Color and Texture Fused Features

Application of Content-based Image Retrieval in Remote Sensing Images

Image Retrieval of Rice Varieties Database Using Computer Vision

A novel classification-coding scheme for medical image retrieval

Review of Relevance Feedback Algorithms in Content-based Image Retrieval

Connected-Region Histogram Method for Image Retrieval

The Application of Wavelet Modulus Maxima Algorithm in the Image Retrieval

Spatial Clustering Based Image Retrieval Method

Application of Local Color Features in Content-based Image Retrieval

The Methods of Semantics Processing in Content-Based Image Retrieval

Review and research on "semantic gap" problem in the content based image retrieval

Design and Implementation of Shape-based Image Retrieval System

The Design of Content-based Intelligence Image Retrieval System

Research on Image Retrieval Technique Using Both Text and Color Features

Research on the Indexing Technique in Content Based Image Retrieval

Research on Application Condition of Image Retrieval

Fuzzy Histogram Approaches for Color Image Retrieval

Novel Fast Rotation Invariant Image Retrieval Method

A Texture Cluster Indexing Scheme for Content-based Image Retrieval

Region Based Color Image Retrieval Using Color and Texture Features

Algorithm for Semi-Supervised Learning in Image Retrieval

Several Issues of Content-Based Remote Sensing Image Retrieval

Research on Sub-image Feature Fusion Rules in Trademark Image Retrieval

Image retrieval using spatial texture features

Color Image Retrieval Approach with Robustness

Medical image retrieval using metric histogram

Study on Extraction of the Texture Feature in Process of Image Retrieval

A Combined Method of Multiple Level Query Result for Content-based Image Retrieval

A Novel Approach Supporting Multi-image Queries in Image Retrieval

The Analysis of Development of Compressed Image Retrieval Technologies

Image Retrieval Algorithm Based on Global Color and its Implementation

Ordinal Regression in Content-Based Image Retrieval

Shape-based image retrieval using wavelet transform

Image retrieval method using wavelet salient points

Development and prospect on emotion image retrieval

Image retrieval system researching on design patent

Feedback Mechanism of Content-based Image Retrieval

Block k-color Vector Quantization Approach to Image Retrieval

Texture Image Retrieval Based Complex Wavelet and KL Distance

An Improved Color Matching Pair Algorithm for Image Retrieval

Application of multi-band wavelets to medical image retrieval

A Feature Selection Based Approach in Medical Image Retrieval

Key Technologies of Content-based Image Retrieval System

Using Invariant Feature in Content-Based Image Retrieval

A Dynamic Similarity Metric Approach for Image Retrieval

A Method for Image Retrieval Technique Based on Local Distribution Features of Interest Points

Implementation of an Image Retrieval System Based on Multimedia Fusion

image retrieval based on wavelet - based region segmentation and statistical properties

A Neural Network Based Self-Learning Algorithm of Image Retrieval

Image Retrieval Using Both Texture and Image Center Features

Research on Texture-Based Semantic Image Retrieval

Application of Immune Algorithm in Image Retrieval

A Grey Relevance Feedback Algorithm for Image Retrieval

Algorithms of High-Level Semantic-Based Image Retrieval

Novel shape- based image retrieval using direction code

Image Retrieval Using Difference Matrix

A Novel Dynamic Sub-Region Running Algorithm for Image Retrieval

Image Retrieval Technique in the Compressed Domain: A Review

Comparative Studies on Similarity Measures for Remote Sensing Image Retrieval Based on Histogram

An Approach to Automatic Layout Analysis in Image Retrieval

The Application of Fast Wavelet Entropy For Image Retrieval

Content-Based Image Retrieval Key Techniques

The Design of Agent Using the Feedback Information in Intelligent Image Retrieval System

a survey on content - based image retrieval techniques

Rough Set Feature Weighting Method for Image Retrieval

The Application of Geometric Moment Invariants in Field of Content-Based Medical Image Retrieval

Some Methods about Content- Based Image Retrieval

Image Retrieval of Standard Tobacco Leaf Database

Color Extraction and Matching for Image Retrieval

Feature Analysis of Content-Based Image Retrieval

Content- based medical image retrieval

Application of AAM Image Retrieval Technique in Modern War