Abstract
A statistical approach, based on a family of Full Range Autoregressive models, is proposed for texture analysis. Bayesian approach is adopted to estimate the model parameters. Using the parameters, autocorrelation (AC) coefficient is computed. Based on the AC, two texture descriptors are proposed: (i) texnum, the local descriptor and (ii) texspectrum, the global descriptor. Decimal numbers are computed and that are proposed to represent textures present in a small image region. These numbers uniquely represent the texture primitives. The textured image under analysis is represented globally by observing the frequency of occurrences of the texnums called texspectrum. The textures are identified and are distinguished from the untextured regions with edges.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
