IEEE Trans Image Process - QR images: optimized image embedding in QR codes.

Tópicos

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Resumo

This paper introduces the concept of QR images, an automatic method to embed QR codes into color images with bounded probability of detection error. These embeddings are compatible with standard decoding applications and can be applied to any color image with full area coverage. The QR information bits are encoded into the luminance values of the image, taking advantage of the immunity of QR readers against local luminance disturbances. To mitigate the visual distortion of the QR image, the algorithm utilizes halftoning masks for the selection of modified pixels and nonlinear programming techniques to locally optimize luminance levels. A tractable model for the probability of error is developed and models of the human visual system are considered in the quality metric used to optimize the luminance levels of the QR image. To minimize the processing time, the optimization techniques proposed to consider the mechanics of a common binarization method and are designed to be amenable for parallel implementations. Experimental results show the graceful degradation of the decoding rate and the perceptual quality as a function the embedding parameters. A visual comparison between the proposed and existing methods is presented.

Resumo Limpo

paper introduc concept qr imag automat method emb qr code color imag bound probabl detect error embed compat standard decod applic can appli color imag full area coverag qr inform bit encod lumin valu imag take advantag immun qr reader local lumin disturb mitig visual distort qr imag algorithm util halfton mask select modifi pixel nonlinear program techniqu local optim lumin level tractabl model probabl error develop model human visual system consid qualiti metric use optim lumin level qr imag minim process time optim techniqu propos consid mechan common binar method design amen parallel implement experiment result show grace degrad decod rate perceptu qualiti function embed paramet visual comparison propos exist method present

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