Colored Image Segmentation using K-Means Algorithm
DOI:
https://doi.org/10.24297/ijct.v15i7.1559Keywords:
Background subtraction, Hand gesture recognition, HSV, RGB, YCbCr, Multi-class SVMAbstract
Hand gestures are natural means of communication for human beings and even more so for hearing and speech impaired people who communicate through sign language. Unfortunately, most people are not familiar with sign language and an interpreter is required to translate dialogues. Hence, there is a need to develop a low cost, easily implementable and efficient means to recognize sign language gestures to eliminate the interpreter and facilitate easier communication. The proposed work achieves a satisfactory recognition accuracy using in-built laptop webcam using combination of 3 skin color models(HSV,RGB,YCbCr) and background subtraction to eliminate noise from webcam low quality images to recognize sign language for helping the hearing and speech impaired in real-time without requiring too much computational power or any other device as it can be implemented in any laptop with a webcam.