On-line quality control assessment of the production process of preserved orange segments

This paper describes an automated visual inspection (AVI) system for quality control of preserved orange segments, which can be widely applied to production processes of preserved fruits and vegetables. Main constraints concerning these kinds of inspection applications are addressed: the need of on-line operation together with a strong requirement of economic profitability. The strong commitment of above circumstances has forced the development of a flexible and low cost AVI architecture. The data volume to be processed forced up the development of sophisticated control architecture for high-speed machine vision applications. Special effort has been put in the design of the defect detection algorithms to reach two main objectives: accurate feature extraction and on-line capabilities, both considering robustness and low processing time. These goals have been achieved combining a local analysis together with data interpretation based on syntactical analysis, which has allowed avoiding morphological analysis. An on-line implementation to inspect up to ten orange segments per second is reported.

[1]  V. J. Davidson,et al.  Fuzzy methods for automated inspection of food products , 1999, 18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397).

[2]  David Alan Bourne,et al.  Manufacturing intelligence , 1988 .

[3]  W. Pölzleitner,et al.  Real-time surface grading of profiled wooden boards , 1992 .

[4]  Anup Basu,et al.  Computer Vision: Systems, Theory and Applications , 1993, World Scientific Series in Computer Science.

[5]  B. Smith Six-sigma design (quality control) , 1993, IEEE Spectrum.

[6]  D. H. Baillie,et al.  Multivariate Acceptance Sampling , 1987 .

[7]  Ming-Kuei Hu,et al.  Visual pattern recognition by moment invariants , 1962, IRE Trans. Inf. Theory.