Indian Journal of Science and Technology
Year: 2020, Volume: 13, Issue: 27, Pages: 2755-2773
B Srinivas1*, V Venkata Krishna2, L Sumalatha3
1Research Scholar, JNTU Kakinada, Asst. Professor, Anurag Group of Institutions (Autonomous), Hyderabad, Telangana, India
2Professor, Vasavi College of Engineering, Hyderabad, Telangana, India
3Professor, University College of Engineering, JNTUK, Kakinada, Andhra Pradesh, India
Email: [email protected]
Received Date:25 May 2020, Accepted Date:08 July 2020, Published Date:31 July 2020
Objectives: The main goal of this study is to derive an efficient feature vector to capture both the color and texture information. This makes the proposed descriptor as a multipurpose descriptor. Methodology: This study derived color information by combining the individual histograms of H, S and V plane. A texture descriptor is derived by considering the relationship: i) between pairs of symmetric cross pixels and ii) between pairs of symmetric diagonal pixels of the 3 x 3 neighborhood. The relationship is derived using XOR and AND logical functions. Findings: This study derived a unique six bit code and constructed a co-occurrence matrix. The GLCM features are derived on this. To reduce the complexity, this study also derived another descriptor by indexing the six bit code using the rotational invariant property. Novelty: The proposed color and texture descriptors give better results, and a significant improvement is achieved in this study by concatenating these two descriptors for CBIR.
Keywords: CBIR; firstorder; symmetric; derivatives; histogram; indexed; GLCM
© 2020 Srinivas, Venkata Krishna, Sumalatha. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee).
Subscribe now for latest articles and news.