Current Pedorthics | January-February 2020 | Vol.52, Issue 1 | Page 25

Mobile Application for Ulcer Detection Figure 1: Flow chart of the overall system. START Calculate Foot - Suspected Mean Temperature (FS) IMAGE ACQUISITION Calculate - Suspected Mean Temperature (S) — TD Extract RGB Image Extract Radiometric Data (1D) TD<=2.20 Remove Background Convert to 2D TD>2.20 Convert to greyscale S<25 && FS<25 Remove Background 1 No Ulcer 1 Ulcer 1 — S>50 && FS>50 Foot Suspected Smoothening Extract Suspected Region with values ranging from 0 to 255. These values for the radiometric data were obtained in Kelvin times one hundred. A single channel grayscale image can be constructed and shown when displayed. To understand the displayed image, the data in the grayscale image ranges in a color scale of 0-255. The zero value represents the lowest temperature from the actual radiometric data, and the 255 value represents the highest temperature. Moreover, the scaled values were used to BGR Foot Highlight Ulcer Region No Ulcer 1 1 No Ulcer 0 ULCER? Display with Readings BGR Foot w / o background END extract portions of the image following an image segmentation procedure. Applying a binary threshold to the grayscale helps in segmenting the feet of the patient from any background structures. This is based on the idea of temperature variation between the feet segments (Hot) and the background (Cold). A threshold of 149 was applied on the grayscale image to extract the feet segments. The binary image was then eroded to remove any noise (wrongly classified background segments) that Current Pedorthics | January/February 2020 23