Quality Inspection of Bag Packaging Red Beans (Phaseolus vulgaris) Using Fuzzy Clustering Algorithm
Ngatchou Alban *
Institute of Agricultural Research for Development (IRAD), P.O.Box 2067 or 2123 Yaoundé, Cameroon.
Bitjoka Laurent
Modelisation, Image Processing and Applications Research Group (MOTRIMA), Biophysics and Food Biochemistry Laboratory, National school of agro-industrial sciences, The University of Ngaoundéré, P.O.Box 455, Ngaoundéré, Cameroon.
Yemefack Martin
Institute of Agricultural Research for Development (IRAD), P.O.Box 2067 or 2123 Yaoundé, Cameroon.
Boukar Ousman
Modelisation, Image Processing and Applications Research Group (MOTRIMA), Biophysics and Food Biochemistry Laboratory, National school of agro-industrial sciences, The University of Ngaoundéré, P.O.Box 455, Ngaoundéré, Cameroon.
*Author to whom correspondence should be addressed.
Abstract
Food industry is currently focusing on fast and unsupervised quality inspection techniques. This paper deals with the development of new method for fast quality control of bag packaging red beans (Phaseolus vulgaris) using flatbed scanning. The proposed method combines fuzzy c means with spatial transformation (FCM_ST) to reduce FCM iteration. We used the labelled pixel, in the clustering image, for the evaluation of grain mixture in acquired image. The performance of the FCM_ST was compared to the standard FCM approach and it reveals itself very good for fast clustering and efficient detection of grain mixture. The detections accuracies of grain mixture in the bag packaging red beans (Phaseolus vulgaris) was 96% for acquired image with presence of other self-colour commercial beans type, 70% with presence of defected cotyledons beans, between 30% to 89% with presence of multi-coloured beans depending on their texture and between 10% to 15% with the presence of low discoloured red beans of same commercial type.
Keywords: Packaging red beans (Phaseolus vulgaris), fuzzy logic, wavelet transform, quality control.