Fingertip Detection: A Fast Method with Natural Hand

TL;DR

This paper introduces a fast, invariant fingertip detection method that isolates the hand from images using color filtering and histogram-based cropping, enabling efficient gesture recognition applications.

Contribution

A novel, time-efficient fingertip detection algorithm that preprocesses images by isolating the hand, reducing computational load for gesture-based systems.

Findings

Method is invariant to hand direction

Preprocessing reduces computation time

Effective fingertip detection demonstrated

Abstract

Many vision based applications have used fingertips to track or manipulate gestures in their applications. Gesture identification is a natural way to pass the signals to the machine, as the human express its feelings most of the time with hand expressions. Here a novel time efficient algorithm has been described for fingertip detection. This method is invariant to hand direction and in preprocessing it cuts only hand part from the full image, hence further computation would be much faster than processing full image. Binary silhouette of the input image is generated using HSV color space based skin filter and hand cropping done based on intensity histogram of the hand image