Texton Based Image Retrieval Using Indexed LBP Transitions

A. Srinivasa Rao; V.Venkata Krishna; Prof.YKSundara Krishna

doi:10.24297/ijct.v13i12.5282

Authors

A. Srinivasa Rao Research Scholoar ,Krishna University, Machilipatnam,Krishna (dt),AP,INDIA
V.Venkata Krishna Professor in CSE Dept.GIET,Rajahmundry,Andhra Pradesh, INDIA
Prof.YKSundara Krishna Professor in CSE Dept. Krishna University, Machilipatnam, Andhra Pradesh, INDIA

DOI:

https://doi.org/10.24297/ijct.v13i12.5282

Keywords:

Image retrieval, rotational invariant, textons, GLCM.

Abstract

The present paper derived a new model of texture image retrieval by integrating the transitions on Local Binary Pattern (LBP) with textons and Grey Level Co-occurrence Matrix (GLCM). The present paper initially derived transitions that occur from 0 to 1 or 1 to 0 in circular manner on LBP. The transitions reduce the 256 LBP codes into five texture features. This reduces the lot of complexity. The LBP codes are rotationally variant. The proposed circular transitions on LBP are rotationally invariant. Textons,which represents the local relationships,are detected on this. The GLCM features are evaluated on the texton based image for efficient image retrieval. The proposed method is experimented on a huge data base of textures collected from Google data base. The experimental result indicates the efficiency of the proposed model.