A Blind Restoration Approach for Defocused Barcode Images

Author(s):  
Shamik Tiwari

Use of a mobile camera for barcode decoding provides high portability and availability but it requires that the recorded barcode image must be accurate representation of the barcode that is available on the product. Barcode scanning is challenging because images may be degraded due to out-of-focus blur at the time of image acquisition. Therefore, image restoration is essential in making image sharp and useful. In case of blind restoration of such barcode images accurate estimation of out-of-focus blur parameter is highly desirable. In this article, a robust method has been proposed for estimating the radius of out-of-focus blur. Finite discrete ridgelet transform has been used to find the features of the blurred image and a radial basis function neural network is utilized to estimate the radius of out-of-focus blur. The experimental results reveal that proposed method more robust than the existing methods.

Medical imaging technology is becoming an important component of large numbers of applications such as diagnosis, treatment, survey and medical examination. Image restoration manages conveying back the bended image to its original domain. It re-establishes the corrupted image into keener image. This paper centers around evacuation of noise strategies in medical images with denoising a point by point overview has been completed on various image denoising methods and their exhibitions were evaluated and it is an activity to examine and evaluate various variations of denoising methods to enhance their execution and visual standard.


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