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An Improved Chromatic Skin Color Model for Detecting Human Skin in JPEG Images


Kaid Saif Almohai, Hani (2005) An Improved Chromatic Skin Color Model for Detecting Human Skin in JPEG Images. Masters thesis, Universiti Putra Malaysia.


The detection of the human skin has proven to be a useful and robust technique in computer vision for detecting, segmenting, and tracking faces and hands. It is also used in many different applications in motion capture, human-computer interaction, access control, surveillance, and content-based image retrieval and indexing of image databases. To build a decision rule that will discriminate between skin and non-skin pixels, a metric has to be introduced to measure the distance of the pixel color to skin tone. The skin color models define the type of this metric.An improved chromatic skin color model is discussed in this thesis. The model detected the human skin in the Bitmap images with JPEG format. A threshold method and 2D Gaussian model were used to improve the accuracy of the skin region detected. Good results have been achieved by using the proposed model. Results show that the model detects the human skin with an excellent detection rates for over than 90%. This result shows that this model is more appropriate to avoid false detection areas, while there remains a high degree of correct detection. This model has been implemented using the MATLAB software, which able to improve the performance and accuracy of skin detection models.

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Additional Metadata

Item Type: Thesis (Masters)
Subject: Human skin color - Colorimetry - Case studies
Subject: Color
Call Number: FK 2005 59
Chairman Supervisor: Associate Professor Abd Rahman Ramli, PhD
Divisions: Faculty of Engineering
Depositing User: Nur Izyan Mohd Zaki
Date Deposited: 10 May 2010 03:41
Last Modified: 13 Jan 2023 03:07
URI: http://psasir.upm.edu.my/id/eprint/6080
Statistic Details: View Download Statistic

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