Implementation of RBG-HS-CbCr skin colour model using mobile python PyS60

Over the past few years, r esearchers have come up with various algorithms and method in detecti ng human skin colour. These algorithms are often tested and applied on PC. The techniques of detecting skin colour are mostly pixel - based and involving fe...

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Bibliographic Details
Main Author: Ngui,, Lin Hui.
Format: Final Year Project Report / IMRAD
Language:English
English
Published: Universiti Malaysia Sarawak, UNIMAS 2009
Subjects:
Online Access:http://ir.unimas.my/id/eprint/6529/
http://ir.unimas.my/id/eprint/6529/1/IMPLEMENTATION%20OF%20RGB-HS-CbCr%20SKIN%20COLOUR%20MODEL%20USING%20MOBILE%20PYTHON%20PyS60%2824%20pgs%29.pdf
http://ir.unimas.my/id/eprint/6529/8/NGUI%20LIN%20HUI.pdf
Description
Summary:Over the past few years, r esearchers have come up with various algorithms and method in detecti ng human skin colour. These algorithms are often tested and applied on PC. The techniques of detecting skin colour are mostly pixel - based and involving few other image processing techniques such as colour segmentation and morphological operation. In this project, however, the concept of colour filtering on dif ferent colour spaces along with pixel looping and setting on the image are used and applied on a Symbian OS mobile phone . This project emphasize the implementation o f RGB - H - CbCr Skin Colour Model, which consi sts of a few sets of bounding rules for separati ng skin colour and non - skin colour region for their pixel values at the RGB, H and CbCr colour subspace. The programming language used in this project is Mobile Python or PyS60 and the written source code is executed on the S60 device mobile platform, whic h is the Nokia N95 in this case. Experimental results are obtained through test s conducted and after several analyses; it is found out that RGB - H - CbCr presents the best algorithm to be used in e xtracting the human skin colour, after a slight modification.