Computer vision for quality grading in fish processing

• Main Author: Misimi, Ekrem
• Other Authors: Norges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for teknisk kybernetikk
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: Fakultet for informasjonsteknologi, matematikk og elektroteknikk 2007
• Subjects: Atlantic salmon
• Online Access: http://hdl.handle.net/11250/259426

High labour costs, due to the existing technology that still involves a high degree of manually based processing, incur overall high production costs in the fish processing industry. Therefore, a higher degree of automation of processing lines is often desirable, and this strategy has been adopted by the Norwegian fish processing industry to cut-down production costs. In fish processing, despite a slower uptake than in other domains of industry, the use of computer vision as a strategy for automation is beginning to gain the necessary maturity for online grading and evaluation of various attributes related to fish quality. This can enable lower production costs and simultaneously increase quality through more consistent and non-destructive evaluation of the fish products. This thesis investigates the possibility for automation of fish processing operations by the application of computer vision. The thesis summarises research conducted towards the development of computer vision-based methods for evaluation of various attributes related to whole fish and flesh quality. A brief summary of the main findings is presented here. By application of computer vision, a method for the inspection of the presence of residual blood in the body cavity of whole Atlantic salmon was developed to determine the adequacy of washing. Inadequate washing of fish after bleeding is quite common in commercial processing plants. By segmenting the body cavity and performing a colour analysis, it was shown that the degree of bleeding correlated well with colour parameters, resulting in correct classification of the fish with residual blood. The developed computer vision-based classifier showed a good agreement with the manual classification of the fish that needed re-washing. The proposed method has potential to automate this type of inspection in fish processing lines. In addition, a computer vision-based classifier for quality grading of whole Atlantic salmon in different grading classes, as specified by the industrial standard, was ...