Untitled Document

Abstract

The scale of picture collecting and data storage technologies is growing, as is the enlargement of quantity and quality of the image DB. Previously, retrieval of photos was accomplished through verbal descriptions and manual labelling of photographs, labour-intensive process. The necessity is for efficient systems termed content-based image retrieval systems to manage big collections. In this situation, the image’s visual contents, such as the shape, layout, and colour of the items included in the picture, are taken into account, as well as the image’s related data. These systems are more efficient and faster than other traditional methods of picture retrieval. In this paper, a novel method for extracting features using Gabor filtering is presented, which is then optimised through lion optimization. Finally, SVM is employed with cuckoo search optimization, while the decision tree technique is used with lion search optimization. The proposed method is put to the test on a variety of parameters, and the results reveal that Lion optimization outperforms cuckoo search.