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IJSTR >> Volume 8 - Issue 10, October 2019 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Hybrid Shape Based Image Retrieval-Performance Improvement Using Parallel Processing

[Full Text]

 

AUTHOR(S)

Girija G. Chiddarwar, S. Phani Kumar

 

KEYWORDS

Shape Based Image Retrieval, Graphics Processing Unit, Locality Sensitive Hashing, Global descriptors, Local descriptors

 

ABSTRACT

Shape-Based Image Retrieval (SBIR) is an image mining process which extracts images based on contents of the query image. SBIR is being used in several applications like medicine, digital libraries, biodiversity information systems, historical research, and crime prevention etc. Generally, SBIR is implemented using either local features (texture, color, intensity, etc.) or global features (edges, points, contours, shape, etc.). Computation of local features for image retrieval gives high precision but low performance; while computation using global features gives high performance by sacrificing precision. To overcome the limitation of local and global features, the proposed method uses hybrid technique. And to make SBIR faster, we tried towards adventure a GPU (graphics processing unit) to parallelize both feature extraction and the similarity matching process. Meanwhile GPUs have numerous processing units; we can apply enormous parallelism in both steps. In similarity matching process, locality sensitive hashing (LSH) is used to convert descriptors to bitsets, which is further used for similarity matching. To conclude, the proposed system has increased the accuracy, precision and retrieval performance as compared with other techniques.

 

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