A ROBUST SOFTWARE BARCODE READER USING THE HOUGH TRANSFORM PDF

A Robust Software Barcode Reader Using the Hough Transform . In this paper we present a method based on the Hough transform which. Published in: · Proceeding. ICIIS ’99 Proceedings of the International Conference on Information Intelligence and Systems. Page March 31 – April A Robust Software Barcode Reader Using the Hough Transform (Englisch). Muniz, R. / Junco, L. / Otero, A. / Institute of Electrical and Electronics Engineers.

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The localization method is based on detecting the areas with the maximum density difference in two normal directions. The choice of an incorrect value of k due to single-digit analysis is likely to result in a robusg segment that does not fit well together with the other segments see Fig. Our technique relies on deformable templates and exploits all the gray level information of each pixel. Roberto Manduchi obtained his Ph.

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Existing approaches for barcode localization apply to the binarized image methods based on Hough transforms [ 6 ], edge orientation histograms [ 14 ], morphological operators [ 4 ], or wavelet transforms [ 13 ]. More precisely, we define the likelihood of the intensity within a generic digit segment for symbol k conditioned on o and w as. These approaches report high accuracy, but unfortunately do not present comparative tests nor make their data sets public.

The Probabilities of Stripe-to-Stripe Combinations. While dramatically decreasing the search time, based on our experiments, this change does not seem to affect the accuracy of the algorithm.

Click here to sign up. International Journal of Image and Graphics. Please note the extremely poor quality of the images by zooming in. Regarding the implementation of this procedure, the following observations are in order:. Our algorithm correctly decodes barcodes even when the image quality is extremely poor, as can be appreciated by zooming in on the images. Due to the presence of the noise, there are some infrequent narrow peaks and valleys appeared in the waveform.

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These points are extracted by thresholding the transformed image taking a suitable threshold. This shows that our algorithm is suitable for mobile applications and also proves that, in the event of failure at reading the barcode, the process can be quickly repeated.

Determining the location of industrial bar-codes using neural networks Image Processing and Its Applications, Sixth International Conference Many cellphone cameras on the market are equipped with low-grade lenses, generally lacking focusing capability, which often produce blurred images.

We define a global cost function that, for each possible sequence of symbols, penalizes overlaps or gaps in the sequence of deformed templates, with the deformation parameters obtained by least squares regression.

Waveform Decoding We introduce a novel method for waveform decoding in this section, considering the EAN13 barcode type as the sample barcode type. Applications of hidden Markov models in bar code decoding.

bagcode It is composed of three functions: Dilation, in general, causes objects to dilate Edge Image or grow in size; while erosion causes objects to shrink. We extensively tested our algorithm showing improved performance with respect to other state-of-the-art software and algorithms, especially for the most challenging images.

On the contrary, we show that due to the particular nature of the model M kand assuming a simple form for the prior p owthe integral in Eq.

The same can be said for edge extraction. Barcode reading has been studied and optimized for decades and it now represents a well established reaer standard.

Reading 1-D Barcodes with Mobile Phones Using Deformable Templates

Although this algorithm relies on the assumption that the bars of the barcode are approximately vertical in the image, our studies show that the map I e n can be segmented even when this assumption is not satisfied. The equations for these lines are easily computed; for the third bar plot dfor instance, we can write: These disadvantages houhh that the barcode has to be manually oriented towards the laser beam to get the barcode value, high cost and the harmfulness for the user from the exposure to the laser beam.

Given an image containing a barcode, two distinct operations are needed for accessing the information contained in the barcode: The implementation is done trahsform such a way that most of the time it will operate on light search and partial search respectively.

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Slftware barcode reader Given an image containing a barcode, two distinct operations are needed for accessing the information contained in the barcode: These Include two-step paradigm of image feature extraction method 1Hough Transformation 2Rearer Networks Method 3 4Texture Analysis 5 and Mathematical Morphology 6 for barcode localization within the image and Selective Sampling method 7EM Algorithm 8 9 and Statistical Pattern Recognition 10 for decoding the sequence.

Reading 1-D Barcodes with Mobile Phones Using Deformable Templates

This also implies that the base width w is constant across the barcode. UPC-A is a technology to encode numbers with 12 decimal digits symbols as an alternating sequence of black bars and white bars spaces with different widths.

The images are all of high resolution, and each image was manually cropped around the barcode. The intensity profile from the segment highlighted in red on the blue scanline is shown in the plot, where the black lines represent the symbols as output by our algorithm.

We now describe in detail each of the steps of this procedure. Currently he is a Ph. Edge Image Figure Once the barcode has been localized, decoding takes place. Barcode Transformation Transformation process is based on Hough line detection method. A sample of images correctly decoded by our algorithm is shown in Fig. A threshold selection method from gray-level histograms.

This, in turn, is due to the very nature of the scanline which is itself piecewise constant: We then define a likelihood function to measure how well teh deformed shifted and scaled template explains the observed intensity. In our approach, as indicated in barccode figure, first original image is converted to edge image.