Quick response barcode deblurring via L ₀ regularisation based sparse optimisation

Optimal path for automated pedestrian detection: image deblurring algorithm based on generative adversarial network

“…The ID algorithm in view of the GAN is compared with the CNN deblurring algorithm in view of the real dynamic scene, the cGAN based deblurring algorithm and the generalized mathematical L0 sparse expression based deblurring algorithm [21][22][23]. The index outcomes are demonstrated in Fig.…”

Blur-readable two-dimensional barcode based on blur-invariant shape and geometric features

“…In recent years, machine learning and deep learning are used in blurry 2D barcode images, 6,7 but these methods rely on the quality and large quantity of the image samples, which might not be applicable to the practical scenarios. 16 The 2D barcode images are very different from natural images, and they are usually composed of finder patterns and data regions. Finder patterns enable their positions to be quickly located and data regions encode data.…”

“…14 In practical applications, blurring is one of the common degradations in captured 2D barcode images and the identification and verification of the blurry 2D barcode images still remain a challenge. 15,16 Many methods have been proposed to deblur 2D barcode images. [16][17][18] However, image deblurring is an ill-posed problem, [19][20][21] and these deblurring methods suffer from expensive time cost due to complicated preprocessing and edge detection algorithms.…”

“…15,16 Many methods have been proposed to deblur 2D barcode images. [16][17][18] However, image deblurring is an ill-posed problem, [19][20][21] and these deblurring methods suffer from expensive time cost due to complicated preprocessing and edge detection algorithms. 6 In addition, ringing artifacts are commonly presented in the deblurred image, [19][20][21] which limits the improvement of decoding accuracy, or even reduces the decoding accuracy.…”