Evaluation of Dissimilarity Measures for Image Retrieval and Classification

In this paper, the performance of 11 different distances for image retrieval and classification, based on color, shape and texture, is evaluated. The precision-recall measure and the correct classification rate of the k-NN classifier are used to evaluate retrieval and classification performances, respectively. The experimental results for a database of 1000 images from 10 different semantic groups, based on color histogram, directional edge histogram and Gabor features are presented and discussed

Evaluation of Dissimilarity Measures for Image Retrieval and Classification Keywords:

Content-based image retrieval , Dissimilarity measure , Low-level feature , Semantic feature , Classification , ماتریس پراکندگی , : الگوریتم ژنتیک , تطبیق مد , فیلترهای موجبری , داپلکسرهای موجبری