@inproceedings{scholars1715, note = {cited By 2; Conference of 3rd National Postgraduate Conference - Energy and Sustainability: Exploring the Innovative Minds, NPC 2011 ; Conference Date: 19 September 2011 Through 20 September 2011; Conference Code:88531}, doi = {10.1109/NatPC.2011.6136308}, year = {2011}, address = {Perak}, title = {Efficient image retrieval based on texture features}, journal = {2011 National Postgraduate Conference - Energy and Sustainability: Exploring the Innovative Minds, NPC 2011}, author = {Fazal-E-Malik, {} and Baharudin, B.}, isbn = {9781457718847}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84857069943&doi=10.1109\%2fNatPC.2011.6136308&partnerID=40&md5=457bf4dfd3c9041fbf10596ea3cb40bc}, keywords = {Block sizes; Color images; Computation speed; Content-Based Image Retrieval; Different sizes; Gray-scale images; Intensity levels; Similar image; statistical texture features; Texture features, Algorithms; Content based retrieval; Feature extraction; Probability distributions; Sustainable development; Textures, Image texture}, abstract = {A quick and accurate algorithm for content-based image retrieval (CBIR) is proposed in this paper. The retrieval of the similar images using proposed algorithm from the database is based on the statistical texture features. The basic idea is to convert the RGB color image into grayscale image to reduce the computation speed and increase efficiency. The grayscale image is divided into blocks of different sizes. The statistical texture features are extracted by using the probability distribution of intensity levels in all blocks. In the experiment, the efficiency of feature extraction and accuracy of the image retrieval are measured for different block size methods using the proposed algorithm. The Corel database was used for testing. As a result the proposed CBIR algorithm provided higher performance in terms of efficiency and accuracy. {\^A}{\copyright} 2011 IEEE.} }