Application of machine vision for detection of foreign matter in wheat grains [electronic resource].

Includes reference.

With the level of automation at every level of food production and the rates at which food is being produced, it is becoming increasingly more important to have systems that can automatically detect foreign matter along the way. The color scheme could make a computer vision system very practical for foreign object detection and removal. Research at laboratory levels has demonstrated that machine vision is an effective method for classification of cereal grains like wheat. Robust machine vision algorithms have been developed and tested to extract morphological, color and textural features of wheat grains and dockage content.

Summary in arabic.

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