Abstract:
An optical character recognition system recognizes character images in a document image comprised of character areas and non-character areas. The system includes a step of obtaining multi-value image data representing the document image, the multi-value image data having a first resolution and comprising plural pixels each having a pixel density value. The system binarizes the multi-value image data to produce binary image data having a second resolution for the document image, the second resolution being greater than the first resolution. The target pixel in the multi-value image data is binarized based on pixels adjacent to the target pixel. The system further includes steps for performing block selection on the binary image data for the document image in order to identify character areas of the document image and non-character areas of the document image, and performing optical character recognition processing on binary image data for the character areas of the document image to obtain computer codes for recognized character images in the character areas.
Abstract:
A method for increasing the accuracy of image data classification in a page analysis system for analyzing image data of a document page. The method includes inputting image data of a document page as pixel data, analyzing the pixel data in order to locate all connected pixels, rectangularizing connected pixel data into blocks, analyzing each of the blocks of pixel data in order to determine the type of image data contained in the block, outputting an attribute corresponding to the type of image data determined in the analyzing step, and performing optical character recognition to attempt to recognize a character of the block of image data in the case that the analyzing step cannot determine the type of image data contained in the block.
Abstract:
Image processing method and apparatus are provided. Image information is inputted. The input image information is divided into a plurality of areas. Radial line segments are extended in upper, lower, left, and right directions from a point in an arbitrary notice area in the divided areas and connection information between the line segments and the input image is detected. Characteristics of the notice area are discriminated in accordance with the connection information detected. The connection information of the areas is a relative position of each area. The image information is dot information. The characteristics to be discriminated are such that the image information of the area is a headline.
Abstract:
Image processing method and apparatus are provided. A histogram of image information is obtained. A peak position is detected from the histogram obtained. A small area is decided by using the detected peak position as a reference. A histogram of the decided small area of the image information is obtained. A specific point is determined from the peak position of the histogram of the small area obtained. The size of small area is decided in accordance with a peak width of the histogram of the image information. The image information is inputted by a scanner. A table can be used as image information and the specific point which is decided is an intersection of ruled lines of the table. A cell area of the table is judged from the intersection decided.
Abstract:
In a character recognition method and apparatus, image information is input, the input image information is displayed, a desired area in the input image information is assigned, the number of characters contained in the assigned area is calculated, and the size of a picture frame for displaying a result of character recognition of the image information is determined according to the calculated number of characters.
Abstract:
A pattern recognizing apparatus comprises a feature vector extractor to extract a feature vector of an input pattern; a converting unit to convert the feature vector extracted by the feature vector extractor into the feature vector which is effective for selection between categories; a classification processing unit for calculating an inner product with a predetermined basic vector for the converted vector after the conversion was performed by the converting unit; and a category selecting unit for selecting and outputting a category group to which the input pattern belongs with reference to a predetermined category table on the basis of the result of the calculation by the classification processing unit.