Abstract: A comprising: processing the image to a text image with a number of text blobs; classifying the text blobs based on a calculation as to whether they will belong to a foreground layer or to a background layer in OCR processing; and generating a quality value of the image based on the classified text blobs. By generating the quality value based on the classified text blobs, pictures in the image, which are not relevant for OCR are not taken into account for assessing the quality of the image. The amount of data to be processed is thereby decreased resulting in a method which can be executed in real-time. Furthermore, as the quality assessment criterion is based on the division of blobs into a foreground and a background layer, i.e. on prior knowledge of the OCR system, it provides a good indication for OCR accuracy.

Abstract: A comprising: processing the image to a text image with a number of text blobs; classifying the text blobs based on a calculation as to whether they will belong to a foreground layer or to a background layer in OCR processing; and generating a quality value of the image based on the classified text blobs. By generating the quality value based on the classified text blobs, pictures in the image, which are not relevant for OCR are not taken into account for assessing the quality of the image. The amount of data to be processed is thereby decreased resulting in a method which can be executed in real-time. Furthermore, as the quality assessment criterion is based on the division of blobs into a foreground and a background layer, i.e. on prior knowledge of the OCR system, it provides a good indication for OCR accuracy.

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.