An Enhanced Feature Extraction Model for the Information Retrieval In Crop Disease Detection

Authors(2) :-Sampathkumar S, Rajeswari R

Fast similarity search has more importance in a large-scale dataset while using for image indexing and retrieval in many applications. Semantic hashing is an efficient way to accelerate similarity search, which designs compact binary codes for a large number of images so that semantically similar images are mapped to close codes. Among various hashing approaches, spectral hashing has shown better performance by learning the binary codes with a spectral graph. And Color is one of the most important and widely used in content analysis and retrieval. However, most promising color descriptors consume massive amounts of computation and storage, which is a serious drawback. One of these promising color techniques in image retrieval is the Color Correlogram (CC), but the technique also suffers from the aforementioned drawbacks. Compact and conceptual Correlogram descriptor can be used to represent color Correlogram. Compact Correlogram uses compact-generalized Correlogram, which compresses color and generalizes the distances of the actual Correlogram descriptor and conceptual Correlogram uses spatial correlations for the dominant color of few images instead of a large number of quantized color used by the original descriptor. These two representations are integrated with multiple instance learning method to indexing and retrieval of images in both text application and in multimedia applications. Multiple-instance learning has been widely used in image indexing for its capability of exploring region-level visual information of images. Semantic hashing with multiple instance learning leads better results compared to other methodology in terms of indexed precision with respect to image pixels and image bits.

Authors and Affiliations

Sampathkumar S
Assistant Professor, Department of Computer Science and Engineering, Sri Eshwar College of Engineering, Coimbatore, India
Rajeswari R
Assistant Professor (Senior Grade), Department of Electrical and Electronics Engineering, Government college of Technology, Coimbatore, India

Color Correlogram, Compact Correlogram, Content-Based Image Retrieval (CBIR).

Publication Details

Published in : Volume 4 | Issue 6 | January-February 2018
Date of Publication : 2018-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 188-194
Manuscript Number : IJSRSET1848130
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Sampathkumar S, Rajeswari R, " An Enhanced Feature Extraction Model for the Information Retrieval In Crop Disease Detection, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 6, pp.188-194, January-February-2018.
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