vioft2nntf2t|tblJournal|Abstract_paper|0xf4ffa4d91d000000774c000001001900 CBIR is a technique to retrieve images semantically relevant to query image from an image database. The challenge in CBIR is to develop a method that should increase the retrieval accuracy and reduce the retrieval time. In order to improve the retrieval accuracy and runtime, a multilevel CBIR approach is proposed in this paper. In the first level, the color attributes like mean and standard deviations are proposed to calculate on HSV color space to retrieve the images with minimum disparity distance from the database. In order to minimize search area, in the second level Local Ternary Pattern is proposed on images which were selected from the first level. Experimental results and comparisons demonstrate the superiority of the proposed approach.
D. Latha1, M. Mohamed Sathik2, Y. Jacob Vetha Raj3
Nesamony Memorial Christian College, India1, Sadakathullah Appa College,, India2, Nesamony Memorial Christian College, India3
Content Based Image Retrieval (CBIR), Gray Level Co-occurrence Matrix (GLCM), Local Binary Patterns (LBP), Local Ternary Pattern (LTP)
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| Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 6 , Issue: 3 , Pages: 1174-1179 )
Date of Publication :
February 2016
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