Detection of head position using chain code algorithm
Nowadays, autonomous vision-based system has been applied to handle human job that reliability and efficiency of any intelligent system gain improvement and enhancement. Human head detection is the first step of an autonomous human recognition system. This thesis focuses on a method to recognize and...
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| Format: | Thesis |
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2007
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| Online Access: | http://eprints.uthm.edu.my/705/ http://eprints.uthm.edu.my/705/1/24_Pages_from_DETECTION_OF_HEAD_POSITION_USING_CHAIN_CODE_ALGORITHM.pdf |
| Summary: | Nowadays, autonomous vision-based system has been applied to handle human job
that reliability and efficiency of any intelligent system gain improvement and
enhancement. Human head detection is the first step of an autonomous human
recognition system. This thesis focuses on a method to recognize and detect a human
at the surveillance or highlighted area boundary based their head beside; a simulation
system of head detection was developed using image processing. The main
contribution of this thesis is it contributes an algorithm of head recognition and
detecting which based on image segmentation, Prewitt edge detection and Chain
Code algorithm. Static or still images are used as input data for simulation process.
The use of Median Filter (MF) method for preprocessing stage is studied and
implemented to make low noise for good signification in an image. Prewitt edge
detecting (PED) has been applied to present boundary of features in the images in
early stage. The image converted to binary image using Threshold Coding (TC) for
difference between boundary and background. Features from the image are train
using the Chain Code Algorithm (CCA) to do recognition of the crux human head
then do detecting process. The low of complexity in mathematical equation is the
factor of chosen this method, compares other techniques. Two environments have been applied to demonstrate the performance of the system, a person or more was
detected for texture background and untextured background. The anahsis. design
and development of simulation system are done in Visual C++. All the methods have
been tested on image data and the experimental results have demonstrated a robust
system.
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