A quality measure of mobile phone captured 2D barcode images

2D barcode based mobile tagging technique has not fully matured yet. One of the difficulties is that mobile phone cameras induce inevitable distortions in captured barcode images. For a variety of reasons to be discussed herein, evaluation of the decodability of a barcode image is needed before the decoding process. We propose a novel blurriness measure to classify the samples according to their decodabilities. The proposed quality measure of 2D barcode image is computed by utilizing distinctive histogram features. Experimental results show that the classification accuracy is as high as 94% in our database which consists of samples captured with different phones and conditions. Comparisons with state-of-art quality measures are also conducted. The proposed method is not sensitive to noise, rotation and scaling. It is also applicable to many popular 2D barcode patterns.