Content Based Image Retrieval is one of the
prominent areas in Computer Vision and Image Processing.
Recognition of handwritten characters has been a popular area
of research for many years and still remains an open problem.
The proposed system uses visual image queries for retrieving
similar images from database of Malayalam handwritten
characters. Local Binary Pattern (LBP) descriptors of the
query images are extracted and those features are compared
with the features of the images in database for retrieving
desired characters. This system with local binary pattern gives
excellent retrieval performance
Description:
Neural Computing and Applications Vol 21(7),pp 1757-1763
Kannan, Balakrishnan; Unnikrishnan, A; Bino, Sebastian V(April , 2012)
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Abstract:
Grey Level Co-occurrence Matrices (GLCM) are one of the earliest techniques used for image texture
analysis. In this paper we defined a new feature called trace extracted from the GLCM and its implications
in texture analysis are discussed in the context of Content Based Image Retrieval (CBIR). The theoretical
extension of GLCM to n-dimensional gray scale images are also discussed. The results indicate that trace
features outperform Haralick features when applied to CBIR.
Description:
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.2, April 2012