Hand Gesture Recognition System Using Kohonen Self-Organizing Map


Authors : Juliet P. Cagampang, Sherwin A. Guirnaldo

Volume/Issue : Volume 2 - 2017, Issue 10 - October

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://goo.gl/jcG63M

Thomson Reuters ResearcherID : https://goo.gl/3bkzwv

Hand gesture is a nonverbal communication which is very useful to the deaf and mute. It is also used as an alternative way to communicate with computers. Hand gesture recognition has a wide range of applications such as recognizing of sign language, interfaces for human-computer interaction, robot control, machine vision, smart surveillance, computer games, keyboards and mice replacement. This paper described a hand gesture recognition system, a vision-based approach, to recognize static hand gesture images using Kohonen Self-Organizing Map (SOM), an artificial neural network which learns to classify data without supervision. A set of 29 hand gesture images representing letters of the alphabet, enter, space and backspace keys were captured using a CMU camera. The images were cropped using a photo editor and the edited images were converted to grayscale using the MATLAB software. These images in 1D form were used as training set for the Kohonen Self-Organizing Map. After the unsupervised training, the system was tested using 29 actual hand gestures and 10 trials for each gesture. The system achieved an average of 91% accuracy with only 9% error. The system’s recognition accuracy may be further improved by increasing the number of epochs in the training phase, experimenting to find a better learning rate, using a high-resolution camera to capture the image more precisely to minimize the amount of background noise resulting to a more defined input feature vector to be fed to the SOM.

Keywords : Artificial Neural Network, Image Processing, Kohonen Self-Organizing Map, Vision-Based Approach.

CALL FOR PAPERS


Paper Submission Last Date
29 - February - 2020

Paper Review Notification
In 1-2 Days

Paper Publishing
In 2-3 Days

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.
Subscribe
OR

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.
Subscribe