Illumination Compensation for 2-D Barcode Recognition Basing Morphologic

Improvement of image quality has been highly demanded in digital imaging systems. This study presents a novel illumination normalization approach for 2-D barcode recognition under varying lighting conditions. MMs (Morphological transformations) are employed to original images using big scale multiple SEs (structuring elements). Then we make use of entropy to fuse images. The performance of proposed methodology is illustrated through the processing of images with different kinds of 2-D barcodes under different backgrounds. The experimental results show that this approach can process different kinds of 2-D barcodes under varying lighting conditions adaptively. Compared with other conventional methods, our proposed approach does a better job in processing 2-D barcode under non-uniform illumination.