Document Details

Document Type : Article In Conference 
Document Title :
Automatic Image Segmentation using Sobel Operator and k-Means Clustering: A Case Study in Volume Measurement System for Food Products
Automatic Image Segmentation using Sobel Operator and k-Means Clustering: A Case Study in Volume Measurement System for Food Products
 
Subject : Computer Science 
Document Language : English 
Abstract : Image segmentation is one of important step in visual inspection of food product using computer vision system. However, segmentation of food product image is not easily performed if the image has low contrast with its background or the background in acquired image is not homogeneous. This paper proposes k-means clustering combined with Sobel operator for automatic food product image segmentation. Sobel operator was used to determine region of interest (ROI) and k-means clustering was then employed to separate object and background in ROI. The area outside ROI was considered as background. The proposed method has been validated using 100 images of food product from ten different types. The validation results show that the proposed segmentation method achieves good segmentation result. 
Conference Name : Conference Name: 2015 International Conference on Science in Information Technology 
Duration : From : 27 October 2015 AH - To : 28 October 2015 AH
From : 27 October 2015 AD - To : 28 October 2015 AD 
Publishing Year : 1436 AH
2015 AD 
Number Of Pages : 5 
Article Type : Article 
Conference Place : Indonesia 
Organizing Body : UAD, UPI, UNMUL, UPNVY, Indonesia 
Added Date : Tuesday, March 8, 2016 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
Anton Satria PrabuwonoSatria Prabuwono, Anton ResearcherDoctorateaprabuwono@kau.edu.sa

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 38355.pdf pdf 

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