Artificial Bee Colony Programming Descriptor for Multi-Class Texture Classification


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Arslan S., ÖZTÜRK C.

APPLIED SCIENCES-BASEL, vol.9, no.9, 2019 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 9 Issue: 9
  • Publication Date: 2019
  • Doi Number: 10.3390/app9091930
  • Journal Name: APPLIED SCIENCES-BASEL
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Keywords: Texture classification, artificial bee colony programming-descriptor, image descriptor, local binary pattern, genetic programming-descriptor
  • Erciyes University Affiliated: Yes

Abstract

Featured Application Texture classification aims to identify textures using few samples. Local Binary Pattern (LBP) and GP-descriptor are most used texture classification algorithms. Artificial Bee Colony Programming-Descriptor (ABCP-Descriptor) evaluates samples to extract mathematical models. Comparative results show that proposed ABCP-Descriptor is a successful texture classification method.