Texture classification and retrieval using random neural network model

Teke A., Atalay V.

6th Biennial IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI 2004), Nevada, United States Of America, 28 - 30 March 2004, pp.109-113 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/iai.2004.1300955
  • City: Nevada
  • Country: United States Of America
  • Page Numbers: pp.109-113
  • Middle East Technical University Affiliated: No

Abstract

Texture is one of the most important characteristics used in computer vision and image processing applications. In this paper, a new texture classification and retrieval method is proposed for texture analysis applications. The technique makes use of the random neural network model. The main aim is to represent textures with parameters which are the random neural network weights and classify and retrieve textures using this texture definition. The net work has neurons that correspond to each image pixel, and the neurons are connected according to neighboring relationship between pixels. The method is tested on images produced by using Brodatz album and texture blocks cut from remotely sensed imagery.