Thresholding analysis on barcode image

Abstract

The barcode systems are widely used in industry includes education, military, business, food and etc. The use of image processing on barcode reader is a way of extending the application to the normal user as most of today’s mobile phone is camera equipped. The only problem with the phone's camera is that the captured image is at low quality. This will affect the process of decoding the barcode. One of the processes is thresholding where the original image will be converted into black and white image. Thus, in this project, analysis on a few existing techniques is done as there are many techniques that have been developed for the thresholding. Then, die best thresholding technique is identified such that it is able to overcome the low quality image. The analysis is based on global and local thresholding for both Otsu’s method and GLCM with entropy technique. For global thresholding, window size of 640x480 is used while window size of 5x5, 10x10 and 20x20 is used for local thresholding. In the analysis, GLCM size is limited to 8, 16 and 32 with spatial distance of 1, 2 and 3. Other than that, the entire offset angle (0, 45, 90 and 135) is considered in this analysis and the threshold level for GLCM is determined by local, joint and global entropy. The result has shown that the best thresholding technique for low quality image is the thresholding that is based on GLCM.