French fries are one of the frozen foods with rising demands in domestic and international markets. Color is one of the critical attributes for quality evaluation of french fries. This study discusses the development of a color computer vision system and the integration of neural network technology for objective color evaluation and classification of french fries. The classification accuracy of a prototype back-propagation network developed for this purpose was found to be 96%.
A color classification program was developed for classifying the corn germplasm into seven different color groups based on kernel colors. This heuristic based rule supervised color classification program has an overall accuracy of 99%.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
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.