Research On Image Classification Algorithm Based On Color Feature

With the development of digital equipment,network and multimedia technology, more and more digital images are created in people's working,learning and daily life. Because digital images appearing explosive growth mode,it is a hot research topic that how to organize the mass image data effectively and how to classification and retrieval the digital image with the image low level characteristids.The content of this paper are listed as follows:First,research on image classification method based on color.Feature extraction is the key technology of content based image retrieval,it decide the classification performance.Since color feature is relatively robust to background complication and independent of image size and orientation,it is widely used in image feature representations.This paper uses HSV color model to quantify color space in the image classification system,and abstracts image feature by the representative color of traditional global histogram and image block separately.The accuracy of these image feature extraction methods for classification is also discussed.Second,research on image classification based on support vector machine.Support vector machine can solve small sample learning problem very well.The aim of learning is not only to get optimal values when samples tend to be infinite,but also to get the optimal solutions under current conditions of information.The detailed algorithmic of support vector machine,using One-Against-Rest SVM method to construct classifiers for each image class,and using sequential minimal optimization(SMO) classification algorithm to implements image classification system based on support vector machine are discussed in this paper.Finally,the implementation of relevance feedback method in image classification is introduced.Because of the weak correlation of low-level features and high-level conception of images and different subjective perception of the system users,this paper introduce relevance feedback technology into image classification system,classify images in the process of the interaction between users and system.The process of relevance feedback can be regarded as a branch of classification in pattern recognition, SVM algorithm is used in the process of relevance feedback learn and classification. The experiment results show that introduce relevance feedback technology to image classification system can improve the precision effectively.