Prashanth Kumar G.

Work place: Dept. Of E&C, Channabasaveshwara Institute of Technology, Gubbi, Tumkur-572216, Karnataka, India

E-mail: prashanth_02@rediffmail.com

Website:

Research Interests: Image Processing, Robotics, Neural Networks, Artificial Intelligence

Biography

Mr. Prashanth Kumar G is working as an Asst. Professor in the Dept. Electronics & communication Engineering, Channabasaveshwara Institute of Technology, Gubbi, Tumkur, Karnataka, India. He obtained his B.E (Electronics and Communication) and M. Tech. (Signal Processing) from Siddaganga Institute of Technology, Tumkur, Karnataka, under VTU Belgaum, Karnataka, India. He has 5years of teaching experience. He has published many papers in various international Journals and conferences. His Areas of interest include Image and video processing, Robotics, Artificial Intelligence and neural networks. Presently He is working on ―Implementation and design of driverless vehicles‖.

Author Articles
Real Time Detection and Tracking of Human Face using Skin Color Segmentation and Region Properties

By Prashanth Kumar G. Shashidhara M.

DOI: https://doi.org/10.5815/ijigsp.2014.08.06, Pub. Date: 8 Jul. 2014

Real time faces detection and face tracking is one of the challenging problems in application like computer human interaction, video surveillance, biometrics etc. In this paper we are presenting an algorithm for real time face detection and tracking using skin color segmentation and region properties.
First segmentation of skin regions from an image is done by using different color models. Skin regions are separated from the image by using thresholding. Then to decide whether these regions contain human face or not we used face features. Our procedure is based on skin color segmentation and human face features (knowledge-based approach). We have used RGB, YCbCr, and HSV color models for skin color segmentation. These color models with thresholds, help to remove non skin like pixel from an image. Each segmented skin regions are tested to know whether region is human face or not, by using human face features based on knowledge of geometrical properties of human face.

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