24 August 2006 Correlation pattern recognition: optimal parameters for quality standards control of chocolate marshmallow candy
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Abstract
This paper describes an in situ image recognition system designed to inspect the quality standards of the chocolate pops during their production. The essence of the recognition system is the localization of the events (i.e., defects) in the input images that affect the quality standards of pops. To this end, processing modules, based on correlation filter, and segmentation of images are employed with the objective of measuring the quality standards. Therefore, we designed the correlation filter and defined a set of features from the correlation plane. The desired values for these parameters are obtained by exploiting information about objects to be rejected in order to find the optimal discrimination capability of the system. Regarding this set of features, the pop can be correctly classified. The efficacy of the system has been tested thoroughly under laboratory conditions using at least 50 images, containing 3 different types of possible defects.
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Jorge L. Flores, G. García-Torales, Cristina Ponce Ávila, "Correlation pattern recognition: optimal parameters for quality standards control of chocolate marshmallow candy", Proc. SPIE 6312, Applications of Digital Image Processing XXIX, 63121O (24 August 2006); doi: 10.1117/12.681354; https://doi.org/10.1117/12.681354
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