Fingertip Detection and Finger Identification for Real-time Hand Gesture Recognition using Kinect

Abstract

Fingertip Detection and finger identification is one of the main challenges of gesture spotting and recognition. The topic is mostly related to the Human computer Interaction(HCI) area. We have proposed a system for detection of fingertip and identification of finger by several steps like pre-processing, processing, hand segmentation, palm point identification, fingertip detection, finger identification. Pre-processing includes the thresholding ,RGB to Grayscale conversion and color & depth calibration. Determining the minimum depth value from the Kinect camera, determining the segmentation threshold, cropping the region of interest and edge detection are the steps of processing. Depth and color segmentation and calibration is done for hand segmentation. For fingertip detection we have merged two existing idea from state of the art in a manner that it minimizes the limitations of both approach. Ellipse fitting technique is applied for palm point determination and point-to-point scanning is done for fingertip locating. For finger identification, we have proposed a new model, 4Y - model based on iterative Hill climbing Algorithm for finger identification. The main contribution in this area would be the new approaches of fingertip detection and finger identification.