Abstract
Today the consumer demands for superior quality and safe food products. In order to obtain healthier products we need to emphasize on superior detection capabilities to identify any presence of foreign materials on them which are responsible for making them unhygienic. Image segmentation is one such technique which is vastly employed in such domains. It identifies the affected portion from the other regions. Hence, we made an effort to apply image segmentation to discover the existence of fungal contagion in food items. In this paper, an attempt has been made to use clustering as an approach in image segmentation. Few improved cluster-based image segmentation techniques like K-Means, MCKM, FEKM and FECA were used on quite a variety of food items to detect the existence of any kind of fungal growth on their surface. The results segmentation obtained were analyzed to verify their effectiveness by using few known performance measures including SC, RMSE, PSNR, MSE, MAE and NAE. The various food images were segmented to obtain both their gray scale and colored results. As per our anticipation, the outcome of FECA based segmentation is by far much sounder in contrast to the other methods. More or less every value of chosen quality measures offer encouraging results for FECA based segmentation technique as compared to the others, which implies accurate identification of fungal growth on food surfaces was achievable.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: International Journal of Engineering and Advanced Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.