Abstract
Plantar pressure imaging technologies play more important role in diabetics’ shoe-last design. The plantar pressure imaging data-set was acquired through pressure sensors system and was preprocessed using typical image process technologies including Gauss filtering, gamma correction, and wavelet transform enhancement in this work. To decrease the computational complexity, edge detection operator with Sobel, Roberts, Prewitt, Log and Canny were applied. Finally, threshold-based method, gray, watershed, feature clustering and fuzzy cluster, region growing-based plantar pressure image segmentation were employed, respectively. Results illustrated that threshold performs the better effectiveness by using analytic hierarchy process evaluation method through a special indices definition. The proposed methods in the research will be potential application and guidance for comfort shoe design for diabetics.
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.
