Hand Gesture Recognition using Convexity Defect
Caroline El Fiorenza1, Sandeep Kumar Barik2, Ankit Prajapati3, Sagar Mahesh4
1Ms. Caroline El Fiorenza, Assistant Professor (O.G.), Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai
2Mr. Ankit Prajapati, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai
3Mr. Sandeep Kumar Barik, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai
4Mr. Sagar Mahesh, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai
Manuscript received on October 12, 2019. | Revised Manuscript received on 22 October, 2019. | Manuscript published on November 10, 2019. | PP: 1161-1165 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4489119119/2019©BEIESP | DOI: 10.35940/ijitee.A4489.119119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: RGB, HSV, Hand Gesture, Background Subtraction, Detection, Feature Extraction, Convexity Defect.
Scope of the Article: Pattern Recognition