Abstract
Segmentation is a key process of 2-D barcode identification. In this study we propose a fast adaptive segmentation method that is based on morphological method which is suitable for kinds of 2-D barcode images with different scale, angle and sort. The algorithm is based on mathematical morphology, the basic idea of the algorithm is to use Multi-scale open reconstruction of mathematical morphology to transform the image continuously, then choose whether to terminate by the results of the adjacent image transformation and finally get the final segmentation results by further processing of the images obtain from termination.The proposed approach is applied in experiments on 2-D barcodes with complicated background. The results indicated that the proposed method is very effective in adaptively 2-D barcode image segmentation.
Highlights
Among the wide range of automatic identifications such as RFID, magnetic card, barcode is becoming increasingly popular in recent years
In this study we have proposed a novel method for segmenting gray-level 2-D barcodes on complex background using multi-scale MM reconstruction
By using of the multi-scale open reconstruction we define the algorithm roughly marks out the located region of barcode image
Summary
Among the wide range of automatic identifications such as RFID, magnetic card, barcode is becoming increasingly popular in recent years. In this study we have proposed a novel method for segmenting gray-level 2-D barcodes on complex background using multi-scale MM reconstruction. In the 1st pass, it Use multi-scale morphological opening reconstruction in the pretreatment images and obtain rough segmentation results. A SE along with its higher order homothetic can process the image features based on shape and size This operation is termed as multi-scale morphology (Pastore et al, 2007). It always contains a series of spurious noise with smaller connected regions. Using disc SE iB to erode original image ƒp we can get eroded gray image ƒi: Propose multi-scale open reconstruction: Erosion can erase image features which are smaller than SE. Take eroded image fi as mark image and original image f as mask image to do geodesic dilation reconstruction:
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