The development and application of image classification techniques to analyze the hair amount for hair transplantation

Abstract

This research is to represent about hair amount analysis using image classification techniques for hair transplantation. The objective is to calculate appropriate hair amount. The research applies image processing methods to analyze the scalp area in images which are processed by hair corner detection. The follicular detection algorithm develops based on Shi-Tomasi corner detector and Good Feature to track method to identify implant location and hair amount. The Shi-Tomasi corner detector and Good Features to track provide best result and most accuracy hair quantity which forecast the efficiency price and cost in hair transplantation process.