International Journal of Intelligent Systems and Applications · 2013 · 16 citations · 3 references
ComputingComputer ScienceQuality ManagementArtificial IntelligenceMachine LearningQuality EngineeringDefect ClassificationDefect DetectionDefect ModelingDefects In CeramicsIndustrial InspectionPattern RecognitionAutomated InspectionAutomated Inspection SystemsAutomatic Visual InspectionComputer Vision For InspectionComputer Vision InspectionMachine Learning-based Defect DetectionMaterial Defect DetectionQuality Inspection Automation
This paper deals with detection of defects in the manufactured ceramic tiles to ensure high density quality. The p roblem is concerned with the automatic inspection of ceramic tiles using Artificial Neural Network (ANN). The performance of the technique has been evaluated theoretically and experimentally on samples. Architecture of the system involves binary matrix p rocessing and utilizat ion of Artificial Neural Network (ANN) to detect defects. The above automatic inspection procedures have been implemented and tested on company floor tiles. The results obtained confirmed the efficiency of the methodology in defect detection in raw t ile and its relevance as a pro mising approach on matrix, as well as included in quality control and inspection programs.
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