Template Matching Approach on out of focus Blurred images using Iterative Wiener Filter and Neural Network

Barcode technology plays an important part in people’s daily lives. Out-of-focus image blur are not handled properly by most modern devices which is based on barcode scanning technologies. In existing system, spatial domain template matching approach is used. This works entirely on spatial domain which is capable of reading linear barcodes from low-resolution images containing severe Out-of-Focus blur. This approach fails to decode barcodes that is affected by image blurring. The result produced by this system is also often too blurred. To detect the barcode that are affected by image blurring, the frequency and spatial domain template matching is proposed. This system works on both spatial and frequency domain where denoising and deblurring of linear barcodes can be carried out by Adaptive filter and Iterative Wiener Filter respectively. In Iterative Wiener Filter, the knowledge about point spread function is not necessary while deblurring. Here templates are generated by extracting some features in an image and stored in database as reference templates. With these reference templates, template matching is performed. This system can handle highly-degraded barcode images containing