Algorithms for Size and Color Detection of Smartphone Images of Chronic Wounds for Healthcare Applications

A mobile app for smartphones and tablets to document pressure ulcers was previously developed. The mobile app is part of the rapidly growing field of mobile health. The mobile app replaces paper-based documentation in a healthcare facility with an electronic record. In a user trial in 2013, a key finding was the high value attributed to wound image (photograph) galleries in the mobile app and wound tracking though graphing progression. Consequently, work was undertaken to enhance the imaging features by developing image analysis algorithms for size and color determination of wounds from wound images taken with an on-board smartphone or tablet camera, using no peripheral hardware or ancillary devices in setting up the image. The reliance solely on the internal smartphone sensors to generate high-accuracy measurements brings novelty to the work and specifically in the field of wound management. The work includes three components. The first component, referred to as mask image, obtains the dimensions of an object in the image. The second component, referred to as camera calibration, reconstructs an image taken on an angle (3-D) referenced back to a 2-D plane. The third algorithm determines the range of colors present in an image, separating the image into three component colors by extracting components from the Red Green Blue format of the image, and converting output to red yellow black. An expert system and/or machine learning is recommended to enhance the correlation of wound color to wound stage.