Determination of visual quality of tomato paste using computerized inspection system and artificial neural networks
An artificial neural network (ANN) integrated computerized inspection system (CIS) was developed to determine tomato paste color in CIE L?, a?, and b? color format and the number and size of dark specks which exist in the product. The usability of CIS in the determination of the number and the size of dark specks in tomato paste were investigated by comparing the results of CIS and human inspectors. While the inspectors had difficulties not only in determination of the specks having a diameter less than 0.2mm but also in correct diameter measurement for all specks, the CIS had good determination and measurement capability. In 99 tomato paste samples, the number of the specks having diameter more than 0.2mm were found by human inspectors and CIS as 233 and 235, respectively. However, the manual inspection gave inaccurate results for the diameter measurement of the specks. In the color evaluation of the tomato paste, strong correlations (R) were found between the results estimated from ANN-integrated CIS and those obtained from colorimeter (0.889, 0.958, 0.907 and 0.987 for L?, a?, b? and a?/b?, respectively). The whole system is adapted to a graphical user interface (GUI) for use by a non-skilled person working in the tomato paste sector. While manual methods need approximately 5min, GUI needs 2025s to determine, count and classify the dark specks and to measure the product color.
tomato paste computerized inspection system artificial neural networks color dark speck