Conference Proceedings

Second International Conference on Advances in Computing, Electronics and Electrical Technology - CEET 2014

Capturing Features for Height Computation Derived With Gaussian Mixture Model

Author(s) : ADOMAR L. ILAO, JENNIFER C. CUA, KEVIN ABRAM B. HERNANDEZ, MEILYNNE S. SUNCHUANGCO

Abstract

Height is a biometric trait which is considered as one of the important parameters for the identification of a person and nutritional status. This study generally aimed to obtain the height of a person through experimental approach utilizing computer vision. The web cam captures group of students into a single image. Canny edge detection is applied for image segmentation and Gaussian Mixture Model (GMM) for background subtraction. Segmented images were evaluated to identify the ideal number of students from a controlled environment lessening computer vision constraints. Data collected from the experiment were subjected to one-way ANOVA and T-Test to analyze the difference between prototype derived height from a captured image and actual height of the student. The prototype was developed using OpenCV library integrated to C# available in Microsoft Studio 2010

Conference Title : Second International Conference on Advances in Computing, Electronics and Electrical Technology - CEET 2014
Conference Date(s) : 20 - 21 December, 2014
Place : G Tower Hotel, Kuala Lumpur, Malaysia
No fo Author(s) : 4
DOI : 10.15224/978-1-63248-034-7-30
Page(s) : 25 - 29
Electronic ISBN : 978-1-63248-034-7
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