Real-time barcode reader using active vision

Abstract

Barcodes are commonly used with merchandise to speed up product checkout at department stores and to keep inventory. A barcode is a machine readable code consisting of a series of bars and spaces printed in defined ratios. The function of the barcode scanner is to “read” the image presented by the bar code. Common handheld scanning technologies include wands and lasers. They have some limitations such as limited depth of field, limited life span due to mechanical wear and the barcodes must reside on flat surfaces. Besides that, barcodes must be aligned in a proper way for reading thus limiting the robustness of these readers. This project is aimed towards improving these limitations, by using an active vision system. This project is to decode the UPC-A and EAN-13 barcodes using an active vision system, consisting of a camera and user-written software. The camera will feed the software with continuous frames of images from the environment. These images are converted to grayscale and some preprocessing is performed. Image is filtered (such as sharpening and noise reduction) and converted to binary. An adaptive thresholding algorithm is used to reduce the effects of uneven illumination. Image is then scanned horizontally, vertically and diagonally for barcodes, thus enabling it to decode rotated barcodes. Error correction and predictive decoding is implemented to improve the speed and accuracy of the system. Overall system performance is benchmarked with existing commercially available software.