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2021 | OriginalPaper | Buchkapitel

Content-Based Image Retrieval Using Local Derivative Laplacian Co-occurrence Pattern

verfasst von : Prashant Srivastava, Manish Khare, Ashish Khare

Erschienen in: Multimedia Technology and Enhanced Learning

Verlag: Springer International Publishing

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Abstract

For accessing images from huge repository in an easy manner, the images are required to be properly indexed. Content-Based Image Retrieval (CBIR) is a field which deals with finding solutions to such problems. This paper proposes a new multiresolution descriptor namely, Local Derivative Laplacian Co-occurrence Pattern (LDLCP) for CBIR. Gray level image is subjected to four-level Laplacian of Gaussian filtering in order to perform multiresolution processing of image. Local Derivative Pattern descriptors of resulting four-level filtered image is computed to extract local information from the image. Finally, the Gray-Level Co-occurrence Matrix is used for constructing feature vector. Corel-1K and Corel-5K datasets have been used to test the proposed descriptor and its performance is measured using precision and recall metrics.

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Titel: Content-Based Image Retrieval Using Local Derivative Laplacian Co-occurrence Pattern
verfasst von: Prashant Srivastava
Manish Khare
Ashish Khare
Verlag: Springer International Publishing
Buch: Multimedia Technology and Enhanced Learning
Print ISBN: 978-3-030-82564-5

Electronic ISBN: 978-3-030-82565-2

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-3-030-82565-2_33

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