Software Based Higher Order Structural Foot Abnormality Detection Using Image Processing
This work addresses foot abnormality detection for medical diagnosis, but it appears incremental as it applies an existing method (modified Brucken index) to a specific domain without claiming major breakthroughs.
The paper tackled the detection of flatfoot and high arch abnormalities by analyzing footprint images using a modified Brucken index through biomedical image processing, aiming to classify these disorders based on geometric parameters.
The entire movement of human body undergoes through a periodic process named Gait Cycle. The structure of human foot is the key element to complete the cycle successfully. Abnormality of this foot structure is an alarming form of congenital disorder which results a classification based on the geometry of the human foot print image. Image processing is one of the most efficient way to determine a number of footprint parameter to detect the severeness of disorder. This paper aims to detect the Flatfoot and High Arch foot abnormalities using one of the footprint parameters named Modified Brucken Index by biomedical image processing.