Development of a machine vision system for automatic date grading using digital reflective near-infrared imaging

Quality evaluation of agricultural and food products is important for processing, inventory control, and marketing. Fruit size and skin delamination are two important quality factors for the date industry, especially for high quality dates such as Medjools. Unlike other near-infrared spectrometric approaches, the developed machine vision system uses reflective near-infrared imaging to evaluate date quality by analyzing two-dimensional images. This paper presents the development and test results of a machine vision system for automatic date quality evaluation for commercial production. Near-infrared imaging, vision algorithms, and a variety of operational details of the system, including cameras, optics, illumination, electronics, control, and fruit carrier are presented. The complete machine vision system has been built, field tested, and installed in a date packing facility. Relative to manual grading, the operational system results in improved grading accuracy and a substantial reduction in operating costs.