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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/5611
Title: A novel feature descriptor for image retrieval by combining modified color histogram and diagonally symmetric co-occurrence texture pattern
Authors: Bhunia A.K.
Bhattacharyya A.
Banerjee P.
Pratim Roy, Partha
Murala S.
Published in: Pattern Analysis and Applications
Abstract: In this paper, we have proposed a novel feature descriptors combining color and texture information collectively. In our proposed color descriptor component, the inter-channel relationship between Hue (H) and Saturation (S) channels in the HSV color space has been explored which was not done earlier. We have quantized the H channel into a number of bins and performed the voting with saturation values and vice versa by following a principle similar to that of the HOG descriptor, where orientation of the gradient is quantized into a certain number of bins and voting is done with gradient magnitude. This helps us to study the nature of variation of saturation with variation in Hue and nature of variation of Hue with the variation in saturation. The texture component of our descriptor considers the co-occurrence relationship between the pixels symmetric about both the diagonals of a 3 × 3 window. Our work is inspired from the work done by Dubey et al. (IEEE Signal Process Lett 22(9):1215–1219, [2015]). These two components, viz. color and texture information individually perform better than existing texture and color descriptors. Moreover, when concatenated the proposed descriptors provide a significant improvement over existing descriptors for content base color image retrieval. The proposed descriptor has been tested for image retrieval on five databases, including texture image databases—MIT-VisTex database and Salzburg texture database and natural scene databases Corel 1K, Corel 5K and Corel 10K. The precision and recall values experimented on these databases are compared with some state-of-art local patterns. The proposed method provided satisfactory results from the experiments. © 2019, Springer-Verlag London Ltd., part of Springer Nature.
Citation: Pattern Analysis and Applications (2019), (): -
URI: https://doi.org/10.1007/s10044-019-00827-x
http://repository.iitr.ac.in/handle/123456789/5611
Issue Date: 2019
Publisher: Springer London
Keywords: Corel 10K
Corel 1K
Corel 5K
Diagonally symmetric co-occurrence pattern
Gray level co-occurrence matrix
Histogram quantization
MIT-VisTex database
STex database
ISSN: 14337541
Author Scopus IDs: 57188719920
57202818480
57202820553
56880478500
26639647100
Author Affiliations: Bhunia, A.K., Department of ECE, Institute of Engineering and Management, Kolkata, India
Bhattacharyya, A., Department of ECE, Institute of Engineering and Management, Kolkata, India
Banerjee, P., Department of CSE, Institute of Engineering and Management, Kolkata, India
Roy, P.P., Department of CSE, Indian Institute of Technology Roorkee, Roorkee, India
Murala, S., Department of EE, Indian Institute of Technology Ropar, Rupnagar, India
Corresponding Author: Bhunia, A.K.; Department of ECE, Institute of Engineering and ManagementIndia; email: ayanbhunia007@gmail.com
Appears in Collections:Journal Publications [CS]

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