CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 8334 > Article
Paper
8 June 2012 Image processing with genetic algorithm in a raisin sorting system based on machine vision
Mahdi Abbasgholipour, Behzad Mohammadi Alasti, Vahdi Abbasgholipour, Ali Derakhshan, Mohammad Abbasgholipour, Sharmin Rahmatfam, Sheyda Rahmatfam, Rahim Habibifar
Author Affiliations +
Proceedings Volume 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012); 83342N (2012) https://doi.org/10.1117/12.956436
Event: Fourth International Conference on Digital Image Processing (ICDIP 2012), 2012, Kuala Lumpur, Malaysia
Abstract
This study was undertaken to develop machine vision-based raisin detection technology. Supervised color image segmentation using a Permutation-coded Genetic Algorithm (GA) identifying regions in Hue-Saturation-Intensity (HSI) color space (GAHSI) for desired and undesired raisin detection was successfully implemented. Images were captured to explore the possibility of using GAHSI to locate desired raisin and undesired raisin regions in color space simultaneously. In this research, images were processed separately using three segmentation method, K-Means clustering in L*a*b* color space and GAHSI for single image, GA for single image in Red-Green-Blue (RGB) color space (GARGB). The GAHSI results provided evidence for the existence and separability of such regions. When compared with cluster analysis-based segmentation results, the GAHSI method showed no significant difference.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Mahdi Abbasgholipour, Behzad Mohammadi Alasti, Vahdi Abbasgholipour, Ali Derakhshan, Mohammad Abbasgholipour, Sharmin Rahmatfam, Sheyda Rahmatfam, and Rahim Habibifar "Image processing with genetic algorithm in a raisin sorting system based on machine vision", Proc. SPIE 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012), 83342N (8 June 2012); https://doi.org/10.1117/12.956436
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 6 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image segmentation
Image processing
Machine vision
Image quality
Genetic algorithms
Cameras
RGB color model
RELATED CONTENT
Textural discrimination in unconstrained environment
Proceedings of SPIE (March 03 2014)
Improving color image segmentation by spatial-color pixel clustering
Proceedings of SPIE (February 14 2015)
Segmentation of color images using genetic algorithm with image histogram
Proceedings of SPIE (February 14 2015)
Perceptually clustering color for image segmentation
Proceedings of SPIE (September 24 2001)
Color image segmentation: a review
Proceedings of SPIE (February 26 2010)
Color image processing for date quality evaluation
Proceedings of SPIE (January 18 2010)
Color image segmentation using optical models
Proceedings of SPIE (August 24 2001)
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top