Open AccessHand Gesture Recognition using Convexity Defect
Author(s) -
Ms. Caroline El Fiorenza*,
Mr. Ankit Prajapati,
Mr. Sandeep Kumar Barik,
Mr. Sagar Mahesh
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.a4489.119119
Subject(s) - gesture , computer science , convexity , computer vision , artificial intelligence , feature (linguistics) , gesture recognition , invariant (physics) , rgb color model , robot , subtraction , conversation , communication , mathematics , arithmetic , linguistics , philosophy , financial economics , economics , mathematical physics , sociology
Gestures are the simplest way of conveying a message, rather simpler than verbal means. It is the most primitive way of conversation. Gestures can also be the easiest and intuitive way of communicating with a computer, they can be used to communicate or convey information to computers, robots, smart appliances and many other pieces of machinery. It can eliminate the use of mouse and keyboard to some extent. The gestures cited are basically the variable positions as well as orientations of the hand. They can be detected by a simple webcam attached to the computer. The image is first changed into its corresponding RGB values and then to HSV values for better handling and feature recognition. The hand is segregated from the background using feature extraction. Then the values are matched in proximity of the coded values. Then the region of interest is calculated using the concept of convexity and background subtraction. The convex defect helps to define the contour efficiently. This method is invariant for different positions or direction of the gesture. It is able to detect the number of fingers individually and efficiently