Abstract:
A method for automatic sorting includes receiving an item (22) in a sequence of items to be sorted, each such item marked with a respective machine-readable identifying code (42, 52, 54) and with respective characters (44, 56) in a location relative to the code that varies from one item to another in the sequence. A position of the code on the item is determined and, responsive to the position of the code, the location of the characters on the item is found. The characters are processed to determine a destination of the item.
Abstract:
A method for finding a predefined object in an image includes selecting a line belonging to the object, the line having a known stroke width and defining a maximum width (56) and a minimum width (58) that together define a range of widths (60) therebetween that contains the stroke width. A feature in the image is found having a feature width within the range, and the feature is processed to determine whether it is a part of the object.
Abstract:
PROBLEM TO BE SOLVED: To estimate a relative threshold corresponding to an intensity difference between a text and a background in an OCR system. SOLUTION: A text pixel is determined in accordance with a result that differences between the value of a pixel 10 and the values of plural pixels separated from the pixel 10 by a prescribed distance are larger than a relative threshold corresponding to an intensity difference between a text and a background or not, an image is subsamplied at a rate corresponding to two pixels for detecting the kernel of the text and an image pixel is binarized only on a tile having the sideface of plural stroke widths and including the kernel of the text by using the estimated threshold. In the determination of a text pixel, which difference out of differences between two pixels located on positions where a circle 12 having a radius equal to stroke width W around a pixel to be analyzed intersects with a row line, a column line and two lines having an 45 deg. angle and the value of the pixel to be analyzed is larger than the relative threshold is examined.
Abstract:
Method of binarization to be used in an OCR system consisting in determining text pixels by checking, for each pixel, that the difference between its value and the values of a plurality of pixels located at a predetermined distance therefrom is greater than a relative threshold corresponding to the difference in intensities between the text and the background of the image, subsampling the image at a rate corresponding to at least two pixels in order to detect kernels of text, and binarizing the image pixels only in tiles of several stroke width sides containing text kernels by using in each tile, an absolute threshold estimated in this tile. The step of determining text pixels consists, for each analyzed pixel, in checking that either one of the differences between the value of the analyzed pixel and the value of the two pixels located at each intersection of a circle (12) centered at the location of the analyzed pixel and having a radius equal to the stroke width with each one of the row line, column line and both lines at the angle of 45 degrees, is greater than the relative threshold.
Abstract:
A method for finding a predefined object in an image includes selecting a line belonging to the object, the line having a known stroke width and defining a maximum width and a minimum width that together define a range of widths therebetween that contains the stroke width. A feature in the image is found having a feature width within the range, and the feature is processed to determine whether it is a part of the object.
Abstract:
A method for finding a predefined object in an image includes selecting a li ne belonging to the object, the line having a known stroke width and defining a maximum width (56) and a minimum width (58) that together define a range of widths (60) therebetween that contains the stroke width. A feature in the image is found having a feature width within the range, and the feature is processed to determine whether it is a part of the object.
Abstract:
A method for finding a predefined object in an image includes selecting a line belonging to the object, the line having a known stroke width and defining a maximum width and a minimum width that together define a range of widths therebetween that contains the stroke width. A feature in the image is found having a feature width within the range, and the feature is processed to determine whether it is a part of the object.
Abstract:
A method for finding a predefined object in an image includes selecting a li ne belonging to the object, the line having a known stroke width and defining a maximum width (56) and a minimum width (58) that together define a range of widths (60) therebetween that contains the stroke width. A feature in the image is found having a feature width within the range, and the feature is processed to determine whether it is a part of the object.
Abstract:
A method for automatic sorting includes receiving an item in a sequence of items to be sorted, each such item marked with a respective machine-readable identifying code and with respective characters in a location relative to the code that varies from one item to another in the sequence. A position of the code on the item is determined and, responsive to the position of the code, the location of the characters on the item is found. The characters are processed to determine a destination of the item.
Abstract:
A method for automatic sorting includes receiving an item (22) in a sequence of items to be sorted, each such item marked with a respective machine- readable identifying code (42, 52, 54) and with respective characters (44, 5 6) in a location relative to the code that varies from one item to another in t he sequence. A position of the code on the item is determined and, responsive t o the position of the code, the location of the characters on the item is foun d. The characters are processed to determine a destination of the item.