The applications of computer vision system and tomographic radar imaging for assessing physical properties of food

• Published in: Journal of food engineering Vol. 61; no. 1; pp. 125 - 135
• Main Authors: Abdullah, M.Z., Guan, L.C., Lim, K.C., Karim, A.A.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 2004
• Subjects: Automated inspection; Dielectric permittivity; Machine vision; Moisture content; Oil palm grading; Quality evaluation; Rice imaging; Travel-time tomography; Dielectric permittivity; Machine vision; Moisture content; Travel-time tomography; Rice imaging; Automated inspection; Quality evaluation; Oil palm grading
• ISSN: 0260-8774; 1873-5770
• DOI: 10.1016/S0260-8774(03)00194-8

In making physical assessment of agricultural materials and foodstuffs, images are undoubtedly the preferred method in representing concepts to human brain. Regardless of the product, from fresh fruits to prepared foods, colour and moisture content are two important attributes which are regularly being sought by food as well as agricultural engineers. Although these attributes can traditionally be assessed with wide assortment of equipment, however, they generally lack spatial resolution since measurements were often integrated over a small area. This paper focuses on image acquisition technologies which can reveal the information of interest in two dimensions using visible and non-visible band of radiation. Respectively, the technologies investigated are the machine vision system and the computerised radar tomography. The first one was applied for colour grading of oil palms and the second one was used to map the moisture content in grain. The vision system correctly classified 92% of the stationary oil palms by four grade categories, and the radar tomography accurately mapped grain anomalies at 1 GHz over 12–39% moisture range.