Vision Systems

Quality Assessment ........................................................... 120 References ............................................................................................................. 120 2.2 Computer Vision for Quality Control........................................................ 126

2.2.1 Introduction ..................................................................................... 126 2.2.2 Image Analysis and Machine Learning .......................................... 127

2.2.2.1 Image Analysis .................................................................. 127 2.2.2.2 Machine Learning.............................................................. 130

2.2.3 Applications .................................................................................... 132 2.2.3.1 Quality Control of Fruits and Vegetables ......................... 132 2.2.3.2 Quality Control of Grain ................................................... 134 2.2.3.3 Quality Control of Other Foods ........................................ 135

2.2.4 Image Features for Quality Evaluation: Usefulness and Limitation ................................................................................. 136

2.2.5 Conclusions ..................................................................................... 138 References ............................................................................................................. 138

The application of machine vision in agriculture has increased considerably in recent years. There are many fields in which machine vision is involved: terrestrial and aerial mapping of natural resources, crop monitoring, precision agriculture, robotics, automatic guidance, nondestructive inspection of product properties, quality control and classification in processing lines and, in general, process automation. Many authors have successfully applied some of the techniques developed in one of these fields to the others, since all of them try to mimic the human sense of sight (Chen et al. 2002; Brosnan and Sun 2004; Sun 2007).