Automatic Image Segmentation using Sobel Operator and k-Means Clustering: A Case Study in Volume Measurement System for Food Products

Siswantoro, Joko and Prabuwono, Anton Satria and Abdullah, Azizi and Bahari, Idrus (2015) Automatic Image Segmentation using Sobel Operator and k-Means Clustering: A Case Study in Volume Measurement System for Food Products. In: The 2015 International Conference on Science in Information Technology (ICSITech 2015) , 27-28 Oktober 2015, Yogyakarta.

[img]
Preview
PDF
1570148091_new_1st_page.pdf

Download (46Kb) | Preview

Abstract

Image segmentation plays an important role in automatic 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 a method for automatic food product image segmentation using Sobel operator and k-means clustering. Sobel operator was used to determine region of interest (ROI). k-means clustering was then used 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 experimental results show that the proposed method achieves good segmentation result.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: food product; segmentation; Sobel operator; kmeans clustering
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering > Department of Informatic
Depositing User: Joko Siswantoro
Date Deposited: 02 Nov 2015 06:52
Last Modified: 02 Nov 2015 06:52
URI: http://repository.ubaya.ac.id/id/eprint/25843

Actions (login required)

View Item View Item