期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2004
卷号：XXXV Part B3
页码：477-482
出版社：Copernicus Publications
摘要：Mass production of crop, produce, and food staff has resulted in great increase in the efficiency of food producing plants. This in turn has led to considerable decline in food prices. However, the mass production of food was also associated with two major problems. The first one is the decline in food quality, and the second one is the "waste" problem associated with processing and preparation operations. The wastage in many cases is a direct consequence of the quality problem, where the quality decline reaches unaccepted limits. Hence, is the need for quality inspection and assurance mechanisms to be installed in the production lines of such mass food processing and producing plants. In this paper, quality control and inspection system relying on image processing techniques will be discussed and presented in details. 2D and 3D visual characteristics are collected about three kinds of food products that are in one way or another go through a mass production process. These products are Arabic style pita bread and Mexican tortillas. Visual characteristics of interest for this study are collected during the baking phase for the first two products and during classifying and sorting process for the last one. Characters measured for the products were size (width, length, volume, and area), shape, and color (dominant color, localized colors, average color). Imaging system utilizing 5-megapixel digital camera was used to acquire the images for this study. Different image processing procedures like filtering, binarizing, zoning, masking, and enhancement were used to derive the quality control parameters from the visual characters of the products under investigation. This study has shown that machine-based inspection of food products can be implemented effectively, reducing or even eliminating the need for both intensive human intervention and addition of conditioning chemicals to assure quality. The concept and results presented in this study can be applied in solving more complicated pattern recognition problems
