This paper discusses the possibilities of an automated solution for determining dimensionally accurate and defective products using a computer vision system. In a real industrial environment, research was conducted on a prototype of a quality control machine, i.e. a machine that, based on product images, evaluates whether the product is accurate or defective using computer vision. Various geometric features are extracted from the obtained images of products, on the basis of which a fuzzy inference system based on Fuzzy C-means clustering features is created. The extracted geometric features represent the input variables, and the output variable has two values - true and false. The root mean square error in the evaluation of the accuracy and defectiveness of products ranges between 0.07 and 0.16. Through this research, valuable findings and conclusions were reached for the future research, since this topic is poorly examined in the most renowned databases.


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    Title :

    Possibilities of Evaluating the Dimensional Acceptability of Workpieces Using Computer Vision


    Contributors:

    Publication date :

    2023-01-01


    Remarks:

    Tehnički glasnik ; ISSN 1846-6168 (Print) ; ISSN 1848-5588 (Online) ; Volume 17 ; Issue 1


    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629 / 670



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