Abstract
Segmentation has crucial applications in computer vision, pattern recognition, and the processing of digital information. Video segmentation is a problem that crops up in lots of different contexts, such VOD, DVR, e-learning, GIS, and other similar systems. Pixels are roughly separated using a membership grading system that relies on a way of expanding the basic area. Motion capture and clustering of video segmentation is a major hurdle to overcome when obtaining and storing video data. Fuzzy c-means clustering is used here to divide up a movie into its constituent parts. Fuzzy theory provides a framework for describing scene changes based on fuzzy judgements. Because the data space is partitioned appropriately by the membership functions. The suggested method achieves a high degree of accuracy at a low rate of error.
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 callMore From: Turkish Journal of Computer and Mathematics Education (TURCOMAT)
Disclaimer: 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.
