The Application Of Color-Based Image Retrieval In Art Education

Nowadays, quality education makes art education play a more important role in education .Art education, especially esthetics education, needs abundant image resources to broad students' thinking space. Thanks to the advanced development of computer technology and multimedia, the internet offers such resources, and we can put the resources collected by ourselves on the school internet to share with others. Network has become an important access to information people need, which makes image -retrieval from the internet becomes particularly important.There are two methods for the image retrieval: text-based image retrieval and content-based image retrieval. Content-based image retrieval (CBIR) methods is one of most active research points in the fields of image retrieval. It sets up index database of image features through analyzing and extracting image' s content features (such as color, shape, texture, etc.), then retrieve images according to the similarity of image' s content features, which makes the retrieval results have better consistence on visual features. In content-based image retrieval, color is the most intuitionistic and obvious visual feature. Content-based image retrieval realizes the image retrieval through distilling the color features of image with the help of the similarity among color features.To extract color features, for one thing, reasonable color model should be chosen to show color. Though RGB is often used, it doesn' t accord with people' s subjective judgment towards color similarity. So HSV is often applied to the analysis of image colors. Then after making reasonable measuring on color space, we can utilize the color features...