Semantic Web-based Image Retrieval Algorithm

Currently we are using the Internet, the computer on the text, images, video and other information has only a storage, transmission function, its meaning can not be identified, understood and addressed.Semantic Web is the current expansion of the existing computer network, which provides semantic description of the data itself, to achieve an intelligent interaction between different computers, so that a global Web services platform for information sharing intelligence. Image search in Internet networks, automatic classification of digital photos, and satellite remote sensing image classification medical image processing has a very wide application.The main work includes:On the color quantization and color feature extraction depth study. For more accurate extraction of color features and convenience of the back of the semantic classification, the introduction of a block-based color image quantization codebook distribution histogram of code words to describe the color characteristics of the image. A pyramid PHOG gradient direction histogram descriptor, it is a good description of local shape features and shape of the distribution of the spatial layout.Combined with the color code books and PHOG image retrieval method in the experiment achieved good results.SVM Support Vector Machines using a decision tree-level framework for the establishment of the ontological framework of the previous classification, to achieve the semantic-based image retrieval.Images of the same semantic class in accordance with the query's similarity RANK case diagram, the paper presents a new measure known as the serial number for each other like a better measure of similarity between images of each other, while the traditional method RANK be improved to make it more consistent with human perception of image similarity. In the experiment, achieved good results...