Local Painted Texture Pattern for Quality of Content Based Image Retrieval

T. Sivaprakasam and A. Ayyasamy
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T. Sivaprakasam: Alagappa Government Polytechnic College, Department of Computer Engineering
A. Ayyasamy: Government Polytechnic College, Department of Computer Engineering

A chapter in New Trends in Computational Vision and Bio-inspired Computing, 2020, pp 1561-1567 from Springer

Abstract: Abstract Texture is a prevailing tool for feature extraction. This paper determines Local Painted Texture Pattern (LPTP) which gives the local chromatic texture data of an image. The data is extorted independently from the co-related pixel values of assorted channels. It affords the exceptional channel-wise data and it’s related with neighboring pixel data of opponent space. A feature level fusion framework is used to merge Colored Pattern Appearance Model (CPAM) along with LPTP in natural and face databases, which shows significant improvement. The experimental result by using this descriptor presents significant development from the related works for content-based image retrieval and face recognition.

Keywords: CBIR; LPTP; IR; Texture descriptor (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-41862-5_160

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DOI: 10.1007/978-3-030-41862-5_160

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