A Hybrid Soft-computing Method for Image Analysis of Digital Plantar Scanners

• Published in: Journal of medical signals and sensors Vol. 3; no. 1; pp. 15 - 21
• Main Authors: Razjouyan, Javad, Khayat, Omid, Siahi, Mehdi, Mansouri, AliAlizadeh
• Format: Journal Article
• Language: English
• Published: India Medknow Publications & Media Pvt Ltd 2013; Wolters Kluwer Medknow Publications
• Subjects: Anthropometric measurements; bi-level image thresholding; digital plantar image; evolutionary algorithm; foot scanner device; gray level spatial correlation histogram; Original; bi-level image thresholding; digital plantar image; Anthropometric measurements; foot scanner device; evolutionary algorithm; gray level spatial correlation histogram
• ISSN: 2228-7477; 2228-7477
• DOI: 10.4103/2228-7477.114304

Digital foot scanners have been developed in recent years to yield anthropometrists digital image of insole with pressure distribution and anthropometric information. In this paper, a hybrid algorithm containing gray level spatial correlation (GLSC) histogram and Shanbag entropy is presented for analysis of scanned foot images. An evolutionary algorithm is also employed to find the optimum parameters of GLSC and transform function of the membership values. Resulting binary images as the thresholded images are undergone anthropometric measurements taking in to account the scale factor of pixel size to metric scale. The proposed method is finally applied to plantar images obtained through scanning feet of randomly selected subjects by a foot scanner system as our experimental setup described in the paper. Running computation time and the effects of GLSC parameters are investigated in the simulation results.