The Internet of Things Beverages Bottle Shape Defect Detection using Naïve Bayes Classifier - Abdul Rahman, N.N.S.; Saad, N.M.; Abdullah, A. R.; Abdul Wahab, F. (International Journal of Human and Technology Interaction (IJHaTI), 2018)
This paper presents an automated computer vision system using internet of things (IoT) platform for shape defect detection. The proposed system used beverage bottles as a tested product. Morphological operation is applied to segment the image using erosion and dilation process. The features of shape bottle such as area, perimeter, major axis length and extend are extracted. Naïve Bayes classifier is implemented to classify the shape of bottle either pass or rejects based on the estimated extend parameters. All the images are taken using webcam and the captured image is stored in server for wirelessly access. The analysis is done by using image processing toolbox using Matlab in real-time. The result demonstrate that the tested product based on shape is achieved 92% accuracy for good bottle and 90% accuracy for defect bottle using 100 sample images. It shows that the proposed system can be applied for beverages quality control application.