The Internet of Things Beverages Bottle Shape Defect Detection using Naïve Bayes Classifier

This paper presents an automatedcomputer vision system using internet of things(IoT) platform for shape defect detection. Theproposed system used beverage bottles as a testedproduct. Morphological operation is applied tosegment the image using erosion and dilationprocess. The features of shape bottle such asarea, perimeter, major axis length and extend areextracted. Naïve Bayes classifier is implementedto classify the shape of bottle either pass or rejectsbased on the estimated extend parameters. All theimages are taken using webcam and the capturedimage is stored in server for wirelessly access.The analysis is done by using image processingtoolbox using Matlab in real-time. The resultdemonstrate that the tested product based onshape is achieved 92% accuracy for good bottle and90% accuracy for defect bottle using 100 sampleimages. It shows that the proposed system can beapplied for beverages quality control application