Process Neural Network Method: Case Study I: Discrimination of Sweet Red Peppers Prepared by Different Methods
Makaleler > Tam Makale · 2011
Yazarlar: Sevcan Unluturk, Mehmet S. Unluturk, Fikret PAZIR, Alper Kuscu
EURASIP Journal on Advances in Signal Processing, Uluslararası, Wos, 2011, cilt 2011
DOI: 10.1155/2011/290950
Özet
This study utilized a feed-forward neural network model along with computer vision techniques to discriminate sweet red pepper products prepared by different methods such as freezing and pureeing. The differences among the fresh, frozen and pureed samples are investigated by studying their bio-crystallogram images. The dissimilarity in visually analyzed bio-crystallogram images are defined as the distribution of crystals on the circular glass underlay and the thin or the thick structure of crystal needles. However, the visual description and definition of bio-crystallogram images has major disadvantages. A methodology called process neural network (ProcNN) has been studied to overcome these shortcomings.