Automatic footprint detection approach for the calculation of arch index and plantar pressure in a flat rubber pad

To obtain the Arch Index (AI) of footprint, the operation process through a Flat Rubber Pad (FRP) is manually time consuming to realize the necessary foot contact area. To deal with the problem, this paper developed an automatic footprint detection approach by employing the Otsu’s thresholding method and the three components of HSV color space to segment the foot contact boundary in a footprint image. In addition, the ink density pattern of the FRP footprint image represents the pressure with a qualitative description of plantar pressure; the higher the ink density, the higher the pressure. Based on the principle, this paper examined the relationship between the intensity of the gray footprint image and body weight so as to quantify the magnitude of plantar pressures. Therefore, the depths of ink on the footprint image are used for plantar pressure calculation. The experiments verified that the proposed approach incorporated with the FRP can simultaneously obtain both the arch index and the plantar pressure with better accuracy when compared with other existing methods. The advantages of the developed approach with the FRP are that it can help reduce operating time and cost, and automatically obtain the foot contact area for further foot-related calculation without clinical expertise.