Towards Understanding Texture Processing

Gopal Datt Joshi (homepage)

A fundamental goal of texture research is to develop automated computational methods for retrieving visual information and understanding image content based on textural properties in images. A synergy between biological and computer vision research in low-level vision can give substantial insights about the processes for extracting color, edge, motion, and spatial frequency information from images. In this thesis, we seek to understand the texture processing that takes place in low level human vision in order to develop new and effective methods for texture analysis in computer vision. The different representations formed by the early stages of HVS and visual computations carried out by them to handle various texture patterns is of interest. Such information is needed to identify the mechanisms that can be use in texture analysis tasks. We examine two types of cells, namely the bar and grating cells, which have been identified in literature to play an important role in texture processing, and develop functional models for the same. The model for the bar cell is based on the notion of surround inhibition and excitation. Whereas, the model for the grating cell is based on the fact that a grating cell receives direct inputs from the M-type ganglion cells. The representations derived by these cells are used to design solutions to two important problems of texture: texture based segmentation and classification. The former is addressed in the domain of natural image understanding and the latter is addressed in the domain of document image understanding. Based on our work, we conclude that the early stages of HVS effectively represent various texture patterns and also provide ample information to solve the higher level texture analysis tasks. The richness of information emerges from the capability of the HVS to extract global visual primitives from local features. The presented work is an initial attempt to integrate the current knowledge of HVS mechanisms and computational theories developed for texture analysis. (more...) 


Year of completion:
December 2006
 Advisor :

Jayanthi Sivaswamy

Related Publications

  • Joshi Datt Joshi, Saurabh Garg and Jayanthi Sivaswamy - Script Identification from Indian Documents, Proceedings of IAPR Workshop on Document Analysis Systems (DAS 2006), Nelson, pp.255-267. [PDF]

  • Gopal Datt Joshi, Saurabh Garg and Jayanthi Sivaswamy - A Generalised Framework for Script Identification Proc. of International Journal for Document Analysis and Recognition(IJDAR), 10(2), pp.55-68, 2007. [PDF]

  • Gopal Datt Joshi and Jayanthi Sivaswamy - A Computational Model for Boundary Detection, 5th Indian Conference on Computer Vision, Graphics and Image Processing, Madurai, India, LNCS 4338 pp.172-183, 2006. [PDF]

  • Gopal Datt Joshi, and Jayanthi Sivaswamy - A Simple Scheme for Contour Detection, Proceedings of International Conference on Computer Vision and Applications (VISAP 2006), Setubal. [PDF]

  • Gopal Datt Joshi , and Jayanthi Sivaswamy - A Multiscale Approach to Contour Detection, Proceedings of International Conference on Cognition and Recognition ,pp. 183-193, Mysore, 2005. [PDF]