Fast Adaptive Binarization of QR Code Images for Automatic Sorting in Logistics Systems

Abstract

With the development of technology, QR codes play an important role in information exchange. In order to work out the problem of uneven illumination in automatic sorting in logistics systems, an adaptive method in binarization is presented. The proposed method defines the block windows’ size adaptively for local binarization based on the traits of the QR code. It takes advantage of integral images to calculate the sum of gray values in a block. The method can binarize the QR code with high quality and speed under uneven illumination. Compared with several existing algorithms, it is shown that the proposed method is more effective. The experimental results validate that the proposed method has a higher recognition accuracy and is more efficient in binarization.

A Fast Adaptive Binarization Method for QR Code Images Based on Dynamic Illumination Equalization

“…Similarly, the binarization methods proposed by Di et al [10] and Yao et al [11] have not achieved impressive outcomes. This highlights the ongoing innovation in the field, exemplified by recent contributions like the fast adaptive thresholding method proposed by Chen et al [14], to address unevenly illuminated QR code images. Therefore, it is clear that the research landscape is continuously evolving in pursuit of more appropriate solutions for the repair and recognition of unevenly illuminated QR code images.…”

“…Third, the motivation of this work is different from previous studies [13,14], which adopted the structural features of QR code images to optimize the region division determination in the local binarization method, achieving a better binarization effect of unevenly illuminated QR code images. In contrast, this work primarily explores how the structural features of QR code images effectively improve the image enhancement process before binarization.…”

“…In contrast, the approaches based on Yao et al [11], Di et al [10], and Chen et al [13] exhibit binarization outcomes characterized by a loss of vital details. Furthermore, to conduct a quantitative comparison with Chen et al [14], a thorough investigation is conducted based on the PSNR and SSIM across the aforementioned cases. Such metrics can provide a more in-depth evaluation of the performances, shedding light on their abilities to represent the original image while handling uneven illumination.…”

“…However, it has a slow processing speed. Later, Chen et al [14] designed a method that adaptively selects the binary window size based on QR code features and applies the integral image calculation block's sum of gray values to perform the adaptive binarization. Although this approach demonstrates a better image repair quality and good processing speed, it encounters difficulties in accurately detecting the appropriate binarization window size under uneven illumination.…”

QR Codes: From a Survey of the State of the Art to Executable eQR Codes for the Internet of Things

“…Ref. Description Programmability [**] Embedding a program in a QR code to make it executable Anti-counterfeiting [36] Placing hidden information within the QR code to prevent its copy/falsification [37] Use of visual features combined with QR codes to guarantee the authenticity of a product Improving beauty [38] Generation of artistic QR codes, which are embedded in a picture [39] Embedding a QR code within a micrography image [40] Embedding a QR code within a picture [41] Inserting a QR code in a picture by using deep learning technology Improving other technologies [42] Integrating QR codes and RFID technologies to decrease the complexity of RFID circuitry Improving recognition [43] Using an adaptive method based on binarization to improve recognition quality [44] Improving recognition quality when QR codes are placed in an uneven surface [45] Reducing the size of information in a QR code to improve recognition performance [46] A deblurring method is used to improve acquisition quality of QR codes [47] Improving recognition quality of QR code by fastly restoring out-of-focus blurred images [48] Removing perspective by identifying the vertex of a QR code [49] Improve the performance in recognizing multiple QR codes in a picture Increasing capacity [50] Increasing the capacity of a QR code by means of lossless compression [51] Using colored QR codes to improve the storage capacity [52] Improving the encoding efficiency of Chinese characters based on the use frequency Multiple information [53] Embedding three layers of information within one QR code [54] Embedding two layers of information within one QR code [55] Placing a QR code inside another QR code and reading both with different angles Printing type [56] QR codes printed with ink sensitive to pH for quality monitoring of food freshness [57] QR code is printed on a sand core surface for traceability [58] Printing the QR code by caving it on the surface of an object Security [59] Embedding a secret within the QR code by using colors [60] Embedding a secret within the QR code [61] Embedding a secret within the QR code for authentication [...…”