Development of Footprint Analysis Software Using the Cavanagh Arch Index Method Based on a MATLAB GUI

Abstract

The human foot plays a crucial role in supporting body weight and maintaining mobility. It is divided into three main sections: the heel, the arch (middle section), and the forefoot. Based on arch structure, feet are categorized into three types: normal, flat foot, and high arch. Flat feet can negatively affect foot health, making the identification of foot types critical for preventive care. In Indonesia, identification often relies on the wet foot test, which has limitations in accuracy. Therefore, a more effective identification system is needed. Previous studies developed software to identify foot types through digital images, but these lacked advanced features and image quality options. This research aims to develop new software that can operate a scanner, process images directly, and offer flexible editing options for improved image quality. The software was developed using MATLAB r2021B GUI, employing image acquisition and processing toolboxes. The results demonstrate high accuracy, with processing differences of 0.73% for length, 1.22% for width, 1.06% for shoe size, 1.34% for FAC, and 2.49% for the arch index compared to previous software versions.