Pattern Recognition from Segmented Images in Automated Inspection Systems

We present the segmentation of the foreground objects and the identification of the individual objects in the cigarette tin package, so the information will be used for the classification of the acceptable cases or defective cases. Visual inspection and classification of cigarette tin package are very important in manufacturing cigarette products that require high quality package. For the accurate automated inspection and classification, computer vision has been deployed widely in manufacturing. This paper concerned with the problem of identifying the individual cigarette in the tin packing using the image processing and morphology operations. The identified objects can be used for developing a defect finding system in the cigarette packing industries. The approach has two steps: (i) colour-based segmentation of the region of interests, (ii) identifying of individual object. The segmentation performance was evaluated on 18 images including the good cases and the defective cases.