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Image acquisition techniques for assessment of legume quality

Mahajan, Shveta, Das, Amitava, Sardana, Harish Kumar
Trends in food science & technology 2015 v.42 no.2 pp. 116-133
chickpeas, computer vision, food analysis, food grains, insect infestations, lentils, lipid content, peas, seed quality, seeds, soybeans, staple foods, water content
This paper reviews different image acquisition techniques that have been employed for quality evaluation of leguminous seeds and has relevance for engineers, food scientists and other agricultural researchers. The inspection and quality evaluation of food grains using machine vision can be achieved with greater speed, consistency and accuracy. Image acquisition is central to the success of any quality inspection system based on machine vision. Soybeans, peas, beans, lentils and chickpeas are the legumes, which form the staple food and hence have great ecological and economic importance. The image acquisition techniques that are reviewed in this paper are non-destructive in nature and are based on visible, infrared and other bands of the electromagnetic spectrum. These include techniques for external surface examination, measurement of moisture content, oil content, insect infestation detection and internal structure visualization. The advantages of machine-vision techniques over the conventional techniques based on manual methods for seed quality estimation are also discussed.