EFFECTIVE CBIR BASED ON HYBRID IMAGE FEATURES AND MULTILEVEL APPROACH

The instantaneous search and retrieval of the most relevant images to a specific query is one of the significant applications of image processing. The process of retrieval of images using image contents is widely known as content base image retrieval (CBIR). The image features extracted from the local windows of 3*3 resulted good results in CBIR. However, the micro windows of 2*2 derived the texton and motif features and played a dominant role in CBIR. This paper segmented the 3*3 window into two windows namely cross and diagonal windows. Four directional motifs of 1*3 are extracted from each of the cross and diagonal segments. The motif features are derived using Rule based Directional motif (RDM) to address the ambiguity issues. This paper transformed the motif indexes derived on a 1x3 triangular window to a 3*3 window and derived eight triangular RDM local units. The local features are extracted by integrating the features extracted from the eight different images. The extracted features hold directional, textures, patterns, edge properties derived from the 3*3 and triangular windows. The results indicate the superiority of the proposed methods.