Abstract: Presented is a skew detection apparatus. In one form, the apparatus estimates skew based on the locations of a set of foreground content pixels or a set of edge pixels that are nearest to the side of an image of a document. In another form, the apparatus includes a skew estimation unit adapted to estimate skew based on the orientation of foreground or background content in the interior of a document. In another form, the apparatus estimates skew using segments of an image of a document. Also presented is a document image processing apparatus including the skew detection apparatus.

Abstract: Presented is a skew detection apparatus. In one form, the apparatus estimates skew based on the locations of a set of foreground content pixels or a set of edge pixels that are nearest to the side of an image of a document. In another form, the apparatus includes a skew estimation unit adapted to estimate skew based on the orientation of foreground or background content in the interior of a document. In another form, the apparatus estimates skew using segments of an image of a document. Also presented is a document image processing apparatus including the skew detection apparatus.

Abstract: Presented is a skew detection apparatus. In one form, the apparatus estimates skew based on the locations of a set of foreground content pixels or a set of edge pixels that are nearest to the side of an image of a document. In another form, the apparatus includes a skew estimation unit adapted to estimate skew based on the orientation of foreground or background content in the interior of a document. In another form, the apparatus estimates skew using segments of an image of a document. Also presented is a document image processing apparatus including the skew detection apparatus.

Abstract: An edge detection method and apparatus is disclosed. The method comprises the steps of: calculating a pixel gradient value for each of a plurality of pixels of a digital image, the pixel gradient value representing the difference of a pixel value with respect to at least one neighboring pixel; for each of a plurality of binarization threshold values, determining a corresponding edge map representing the location of pixel gradient values exceeding the binarization threshold value with respect to a side of the digital image; for each edge map, computing a measure of linearity; determining an optimal binarization threshold value based on the computed measures of linearity; and selecting the edge map corresponding to the optimal binarization threshold value.

Abstract: Presented is a skew detection apparatus. In one form, the apparatus estimates skew based on the locations of a set of foreground content pixels or a set of edge pixels that are nearest to the side of an image of a document. In another form, the apparatus includes a skew estimation unit adapted to estimate skew based on the orientation of foreground or background content in the interior of a document. In another form, the apparatus estimates skew using segments of an image of a document. Also presented is a document image processing apparatus including the skew detection apparatus.

Abstract: An edge detection method and apparatus is disclosed. The method comprises the steps of: calculating a pixel gradient value for each of a plurality of pixels of a digital image, the pixel gradient value representing the difference of a pixel value with respect to at least one neighbouring pixel; for each of a plurality of binarization threshold values, determining a corresponding edge map representing the location of pixel gradient values exceeding the binarization threshold value with respect to a side of the digital image; for each edge map, computing a measure of linearity; determining an optimal binarization threshold value based on the computed measures of linearity; and selecting the edge map corresponding to the optimal binarization threshold value.