Abstract
The performance of various matrix features in classifying synthetic and natural textures is compared by using the features directly in a maximum likelihood texture classifier (MLTC). The matrix texture features under consideration include the spatial gray level dependence matrix (SGLDM), the neighboring gray level dependence matrix (NGLDM) and the neighboring spatial gray level dependence matrix (NSGLDM). By adopting the MLTC we avoid the various problems associated with the use of scalar features extracted from the matrices under consideration, while we obtain excellent classification results.
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.
