Abstract: A method for aligning a document to a template includes identifying image-bounding rectangles of the document and of the template, identifying center points of the image bounding rectangles and of the document and the template, iteratively transforming the template to match the center points and the image bounding rectangles of the document, and aggregating in a matrix the transformations of the template. The method also includes applying to the document the inverse of the transform matrix.

Abstract: A digital image includes a plurality of pixels arranged in an array. In a method of analyzing the image, some of the pixels are purposefully not processed. In particular, only those pixels in a particular subgroup are processed according to a Hough or similar transform. The number of pixels in the subgroup is less than the total number of pixels in the image (e.g., as little as about 5% of the total pixels), and each pixel in the subgroup is pseudo-randomly selected. The Hough transform is inherently configured to function within the context of noisy images, for identifying features of interest in the image, as simulated by the pseudo-random selection and processing of less than the total number of pixels in the image. This significantly reduces the processor resources required to analyze the image.

Abstract: A method for aligning a document to a template includes identifying image-bounding rectangles of the document and of the template, identifying center points of the image bounding rectangles and of the document and the template, iteratively transforming the template to match the center points and the image bounding rectangles of the document, and aggregating in a matrix the transformations of the template. The method also includes applying to the document the inverse of the transform matrix.

Abstract: A digital image includes a plurality of pixels arranged in an array. In a method of analyzing the image, some of the pixels are purposefully not processed. In particular, only those pixels in a particular subgroup are processed according to a Hough or similar transform. The number of pixels in the subgroup is less than the total number of pixels in the image (e.g., as little as about 5% of the total pixels), and each pixel in the subgroup is pseudo-randomly selected. The Hough transform is inherently configured to function within the context of noisy images, for identifying features of interest in the image, as simulated by the pseudo-random selection and processing of less than the total number of pixels in the image. This significantly reduces the processor resources required to analyze the image.