Author : Yamuna D S 1
Date of Publication :7th May 2016
Abstract: inspecting the empty glass bottles in food manufacturing or in beverage industries is very essential. The cracks in bottles may spoil the contents due to the creation of moisturizing effect inside the bottle. It is necessary to detect such cracks in the bottle. Manual inspection system detects these cracks, which will be inaccurate and time consuming. To overcome this problem many automatic crack detection algorithms are developed. This paper aims at developing empty bottle inspection system using image processing. The empty bottles are tested for defects automatically. The methods developed will detect the cracks on the side surface and bottom surface of the bottle. The image of the defected bottle acquired undergoes pre-processing such as gray scale conversion, noise removal and edge detection. This pre-processed image is analysed for the presence of cracks on the bottles. Adaptive thresholding followed by Raster scan method is used for the analysis of presence of cracks. Algorithms are developed using python which runs on Raspberry pi processor.
Reference :
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[1] Hui-Min Ma, Guang-Da su, Jun-Yan Wang, Zheng Ni, “A Glass bottle defect detection system without touching", in Proc. IEEE International Conference on Machine Learning and Cybeneics, Bejing, pp.628 632, November 2002.
[2] FengDuan, Yaonan Wang, Huanjnn Lin, “A Real-time Machine Vision System for Bottle Finish Inspection", IEEE International Conference on Control, Automation, Robotics and Vision, Kunming, China, pp. 842-846, December 2004.
[3] Sile Ma, Bin Huang, Huajie Wang, Junmei Guo, “Algorithm Re-search on Location of Bottle Mouth and Bottom in Intelligent Empty Bottle Inspection System", IEEE International Conference on Automation and Logistics, Shenyang, China, pp. 819- 824, August 2009.
[4] Huan-jun Liu, Yao-nan Wang, “Development of A Computerized Method to Inspect Empty Glass Bottle", IEEE International Symposium on Computer Science and Computational Technology, pp. 118-123, 2008.
[5] Huanjun Liu, Yaonan Wang, “Development of Glass Bottle Inspector Based on Machine Vision", IEEE 10th International Conference on Control, Automation, Robotics and Vision, Hanoi, Vietnam, pp. 785-790, December 2008.
[6] Feng Duan, Yao-Nan Wang, Huan-Jun LIU, Wen Tan, “Empty bottle inspector based on machine vision", in Proc. IEEE 3rd International Conference on Machine Laming and Cybemetics, Shanghai, pp. 3845-3850, August 2004.
[7] Feng Duan, Yao-Nan Wang, Huan-Jun LIU, Wen Tan, “Empty bottle inspector based on machine vision", in Proc. IEEE 3rd International Conference on Machine Laming and Cybemetics, Shanghai, pp. 3845-3850, August 2004.
[8] Shijie Li, Dapeng Oliver Wu, “Modularity Based Image Segmentation", IEEE Transactions on Circuits and Systems for Video Technology, pp. 4070-4086, April 2015.