Identifying the Defects in Glass Bottles Using Particle Swarm Optimization

This paper aims at designing and developing a suitable tool for identifying defects in glass bottles through visual inspection based on segmentation algorithm. Defects are identified in three stages namely Image acquisition, Pre-processing and filtering and Segmentation. In the Image acquisition stage, samples of real time images are taken and are converted into monochrome images. In the Pre-processing and filtering stage, the image acquired is passed through median filters. The de-noised images are further sent to the third stage which is Segmentation. In this paper, Segmentation is done using Particle Swarm Optimization (PSO). The defects in the images are segmented and highlighted and the areas of defects are spotted out. The Particle Swarm segmentation has produced high Sensitivity, high Specificity, high Accuracy and produced effective results and hence this tool shall be useful for food processing industries for the Quality Inspection of the glass bottles. Keywords--Defects in glass, Filtering, PSO Algorithm, and Segmentation.