Abstract
Thinning algorithms based on morphological hit/miss transforms are good at extracting the skeletons of closed-loop objects in noisy images. However, many skeletal legs are generated usually with unnecessary lengths, and the removal requires much time. This paper investigates fast removal algorithms, and provides a formal performance analysis for algorithms with different arrangements of leg shortening (trimming) templates. First, the use of three algorithms is compared for different image conditions based on probability analysis. Second, to obtain prior information to determine the fastest algorithm, a reduced image is used. Finally, based on this information, a fuzzy-logic approach is used to determine the arrangement of templates. Also, procedures are proposed to form fuzzification functions for the leg properties. An illustration of applying this fuzzy inference mechanism to real-scene images is also included.
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: Engineering Applications of Artificial Intelligence
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.
