Colored Image Segmentation using K-Means Algorithm

Authors

  • Ishita Vishnoi Delhi Technological University
  • Nikunj Khetan Delhi Technological University
  • Sreedevi Indu Delhi Technological University

DOI:

https://doi.org/10.24297/ijct.v15i7.1559

Keywords:

Background subtraction, Hand gesture recognition, HSV, RGB, YCbCr, Multi-class SVM

Abstract

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.

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Author Biographies

  • Ishita Vishnoi, Delhi Technological University
    Department of Computer Science & Engineering
  • Nikunj Khetan, Delhi Technological University
    Department of Computer Science & Engineering
  • Sreedevi Indu, Delhi Technological University
    Associate Professor, Department of Electronics & Communcation Engineering

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Published

2016-05-02

Issue

Section

Research Articles

How to Cite

Colored Image Segmentation using K-Means Algorithm. (2016). INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 15(7), 6950-6956. https://doi.org/10.24297/ijct.v15i7.1559

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