Abstract: The optical character recognition method applies a first OCR engine to provide an identification of characters of at least a first type of characters and zones of at least a second type of characters in the character string image. A second OCR engine is applied on the zones of the at least second type of characters to provide an identification of characters of a second type of characters. The characters identified by the first OCR engine and by the second OCR engine are in a further step combined to obtain the identification of the characters of the character string image.

Abstract: A line segmentation method which starts with determining a first starting point coordinate and generating a list of potential character widths dependent on a maximum character width stored in a database and on characteristics of the portion of the line of text corresponding to the maximum character width. The method determines a second portion of the line of text corresponding to the first starting point coordinate and the first width on the list of potential character widths. On the second portion, a classification method is applied providing a likelihood of error for the first width and a candidate character. The likelihood of error is compared with a first threshold determined by a trade-off between speed and accuracy, and if the likelihood of error corresponding to the first width is lower than the threshold value, the candidate character is selected as the character meaning that a segment is known.

Abstract: A method for identifying a pattern in an image. In a first step the image is normalized to a binary matrix. A binary vector is subsequently generated from the binary matrix. The binary vector is filtered with a sparse matrix to a feature vector using a matrix vector multiplication wherein the matrix vector multiplication determines the values of the feature vector by applying program steps which are the result of transforming the sparse matrix in program steps including conditions on the values of the binary vector.

Abstract: A line segmentation method which starts with determining a first starting point coordinate and generating a list of potential character widths dependent on a maximum character width stored in a database and on characteristics of the portion of the line of text corresponding to the maximum character width. The method determines a second portion of the line of text corresponding to the first starting point coordinate and the first width on the list of potential character widths. On the second portion, a classification method is applied providing a likelihood of error for the first width and a candidate character. The likelihood of error is compared with a first threshold determined by a trade-off between speed and accuracy, and if the likelihood of error corresponding to the first width is lower than the threshold value, the candidate character is selected as the character meaning that a segment is known.

Abstract: A pattern recognition system and method which generates a feature vector by multiplying an image vector with a sparse matrix. The sparse matrix is generated from a Gabor function which is a sinusoidal wave multiplied by a Gaussian function. The Gabor function is a function of a set of parameters including a parameter related to the direction of the sinusoidal wave, a parameter related to a center of the Gabor function, and a parameter related to a wavelength of the sinusoidal wave. The wavelength takes at least two values, with a first wavelength value lower than or substantially equal to the distance between two adjacent centers of the Gabor function, and the first wavelength value is lower than a second wavelength value and higher than or substantially equal to half the second wavelength value.

Abstract: A method for creating a binary mask image from an inputted digital image of a scanned document, including the steps of creating a binarized image by binarizing the inputted digital image, detecting first text regions representing light text on a dark background, and inverting the first text regions, such that the inverted first text regions are interpretable in the same way as dark text on a light background. A method for comparing in a binary image a first pixel blob with a second pixel blob to determine whether they represent matching symbols, including the steps of detecting a line in one blob not present in the other and/or determining if one of the blobs represents an italicized symbol where the other does not.

Abstract: Method, system, device and computer program product for projective correction of an image containing at least one text portion that is distorted by perspective. The method includes a step of image binarization involving binarizing said image. The method includes connected component analysis. Pixel blobs are detected in said at least one text portion of said binarized image in connected component analysis. The method includes horizontal vanishing point determination, including estimating text baselines by means of eigenpoints of said pixel blobs and determining a horizontal vanishing point of said at least one text portion by means of said text baselines. The method also includes vertical vanishing point determination. A vertical vanishing point is determined for said at least one text portion on the basis of vertical features thereof. The method includes projective correction. Perspective in said image is corrected on the basis of said horizontal and vertical vanishing points.

Abstract: Method, system, device and computer program product for determining vanishing point candidates of a text portion in an image document distorted by perspective. The method includes the steps of image binarization, connected component analysis, estimating a number of text lines in a Cartesian coordinate system, transforming the text lines to data points in a homogenous coordinate system, assigning a confidence level to the data points, grouping a number of data points into a priority sample array, clustering the data points in the priority sample array into a number of sample groups and assigning a group confidence value to each sample group. A RANSAC algorithm is applied to determine among the data points a set of inliers, initiated with the sample group having the highest group confidence value. A vanishing point candidate is determined from the text lines corresponding to the set of inliers.

Abstract: Method, system, device and computer program product for projective correction of an image containing at least one text portion that is distorted by perspective. The method includes the steps of image binarization, connected component analysis, horizontal vanishing point determination, vertical vanishing point determination and projective correction. The horizontal vanishing point is determined by estimating text baselines by means of position determining pixels of pixel blobs, identifying horizontal vanishing point candidates from the baselines, and determining a horizontal vanishing point from the candidates. The vertical vanishing point is determined on the basis of vertical features of the text portion. The method includes a first elimination step on the level of position determining pixels, a second elimination step on the level of text baselines and a third elimination step on the level of horizontal vanishing point candidates.

Abstract: Battery-powered portable scanner, comprising: a scanning unit for scanning documents and forming digital representations thereof; a processor, communicatively connected to the scanning unit and provided for controlling the scanning operation; at least a first embedded storage capabilities, each of which is communicatively connected to the processor and each of which comprises either an internal memory for internally storing the digital representations or a communication link to an external storage medium for externally storing the digital representations. The processor is provided for enabling autonomous operation without connection to a terminal. The processor may be provided with an embedded routing application which is provided for routing the digital representations to a predetermined selection among the embedded storage capabilities.

Abstract: A method for creating a binary mask image from an inputted digital image of a scanned document, including the steps of creating a binarized image by binarizing the inputted digital image, detecting first text regions representing light text on a dark background, and inverting the first text regions, such that the inverted first text regions are interpretable in the same way as dark text on a light background. A method for comparing in a binary image a first pixel blob with a second pixel blob to determine whether they represent matching symbols, including the steps of detecting a line in one blob not present in the other and/or determining if one of the blobs represents an italicized symbol where the other does not.

Abstract: Battery-powered portable sheet-fed scanner, comprising: a scanning unit (21-23) for scanning documents and forming digital representations thereof; a sheet feeder (28) for feeding a document past the scanning unit; a processor (20), communicatively connected to the scanning unit and provided for controlling the scanning operation; a plurality of embedded storage capabilities, each of which is communicatively connected to the processor and each of which comprises either an internal memory (26) for internally storing the digital representations or a communication link (24; 25) to an external storage medium for externally storing the digital representations. The processor is provided with an embedded routing application which is provided for routing the digital representations to a predetermined selection among the embedded storage capabilities.

Abstract: A first aspect of the invention relates to a method for creating a binary mask image from an a inputted digital image of a scanned document, comprising the steps of creating a binarized image by binarizing the inputted digital image, detecting first text regions representing light text on a dark background, and inverting the first text regions, such that the inverted first text regions are interpretable in the same way as dark text on a light background. A second aspect of the invention relates to a method for comparing in a binary image a first pixel blob with a second pixel blob to determine whether they represent matching symbols, comprising the steps of detecting a line in one blob not present in the other and/or determining if one of the blobs represents an italicized symbol where the other does not.

Abstract: A pattern recognition process, a non-transitory computer program product, and a mobile terminal for pattern recognition. An input pattern is normalized and a reliable pattern is generated from the normalized pattern by using at least one morphological operator. The distance between the reliable pattern and selected templates which are selected from a template library using a decision tree, is calculated. The reliable patterns are classified into at least one of the classes of the selected templates by at least one non-parametric classification method.

Abstract: Method for up-scaling a color image prior to performing subsequent processing on said color image, comprising the steps of converting the color image into multiple image layers distinguishable from each other and up-scaling at least one of said multiple image layers. The up-scaling is tuned towards the subsequent processing, for example luminance is upscaled at higher quality than chrominance. Further, a method for interpreting information present on digitally acquired documents, comprising the steps of: (i) determining a country; (ii) identifying a list of languages and character sets in use in said country; (iii) performing optical character recognition simultaneously using all languages and character sets of the list; (iv) performing field parsing to identify fields in the digitally acquired document on the basis of international as well as country-specific field recognition rules; (v) storing the recognized information according to the identified fields in a database.

Abstract: Pattern recognition process that includes, starting from an input pattern: normalization of the input pattern into a normalized pattern of predetermined size; generation of a reliable pattern from the normalized pattern by using at least one morphological operator; calculation of a distance between the reliable pattern and selected templates which are selected from a template library; classification of the reliable patterns into at least one of the classes of the selected templates by means of at least one non-parametric classification method, which uses the classes of the selected templates and the calculated distances as inputs and outputs identified classes along with confidence levels.

Abstract: Pattern recognition process that includes, starting from an input pattern: normalization of the input pattern into a normalized pattern of predetermined size; generation of a reliable pattern from the normalized pattern by using at least one morphological operator; calculation of a distance between the reliable pattern and selected templates which are selected from a template library; classification of the reliable patterns into at least one of the classes of the selected templates by means of at least one non-parametric classification method, which uses the classes of the selected templates and the calculated distances as inputs and outputs identified classes along with confidence levels.

Abstract: Method for up-scaling a color image prior to performing subsequent processing on said color image, comprising the steps of converting the color image into multiple image layers distinguishable from each other and up-scaling at least one of said multiple image layers. The up-scaling is tuned towards the subsequent processing, for example luminance is upscaled at higher quality than chrominance. Further, a method for interpreting information present on digitally acquired documents, comprising the steps of: (i) determining a country; (ii) identifying a list of languages and character sets in use in said country; (iii) performing optical character recognition simultaneously using all languages and character sets of the list; (iv) performing field parsing to identify fields in the digitally acquired document on the basis of international as well as country-specific field recognition rules; (v) storing the recognized information according to the identified fields in a database.

Abstract: A first aspect of the invention relates to a method for creating a binary mask image from an a inputted digital image of a scanned document, comprising the steps of creating a binarized image by binarizing the inputted digital image, detecting first text regions representing light text on a dark background, and inverting the first text regions, such that the inverted first text regions are interpretable in the same way as dark text on a light background. A second aspect of the invention relates to a method for comparing in a binary image a first pixel blob with a second pixel blob to determine whether they represent matching symbols, comprising the steps of detecting a line in one blob not present in the other and/or determining if one of the blobs represents an italicized symbol where the other does not.

Abstract: Battery-powered portable scanner, comprising: a scanning unit for scanning documents and forming digital representations thereof; a processor, communicatively connected to the scanning unit and provided for controlling the scanning operation; at least a first embedded storage capabilities, each of which is communicatively connected to the processor and each of which comprises either an internal memory for internally storing the digital representations or a communication link to an external storage medium for externally storing the digital representations. The processor is provided for enabling autonomous operation without connection to a terminal. The processor may be provided with an embedded routing application which is provided for routing the digital representations to a predetermined selection among the embedded storage capabilities.