The invention is a method for omnidirectional recognition of recognizable characters in a captured two-dimensional image. An optical reader configured in accordance with the invention searches for pixel groupings in a starburst pattern, and subjects located pixel groupings to a preliminary edge crawling process which records the pixel position of the grouping's edge and records the count of edge pixels. If two similar-sized pixel groupings are located that are of sizes sufficient to potentially represent recognizable characters, then the reader launches “alignment rails” at pixel positions substantially parallel to a centerline connecting the center points of the two similarly sized groupings. A reader according to the invention searches for additional recognizable characters within the rail area, and subjects each located pixel grouping within the rail area to a shape-characterizing edge crawling process for developing data that characterizes the shape of a pixel grouping's edge. After adjusting the orientation representation of the shape-characterizing data the reader compares the developed shape-characterizing data to previously stored shape-characterizing data to determine the character represented by the grouping on the basis of the best fit data.

Method for omnidirectional processing of 2D images including recognizable characters

Character recognition is described. In one embodiment, it may use matched sequences rather than character shape to determine a computer-legible result.

Method and system for character recognition

In accordance with the present character recognition method, an imaginary stroke is used to link from the ending point of each actual stroke of an input handwritten character to the starting point of the subsequent actual stroke thereof to form a single line. Then a feature level is detected for specifying the position of a turn of the single line and the direction and angle of the turn at the position. According to the detected position of the turn, the detected feature level is patterned on input mesh memories which are in turn compared with a previously formed dictionary mesh memory to calculate the resemblance of the input handwritten character to each handwritten character in a dictionary database. The handwritten character in the dictionary database that has the closest, calculated resemblance is recognized as the input handwritten character. According to the present method, an imaginary stroke added to an input handwritten character also allows correct recognition of a character with each stroke written cursively.

Method and system of handwritten-character recognition

A method and apparatus for differentiating and extracting handwritten annotations and machine printed text in an image. The method provides for the use of morphological operations, preferably at reduced scale, to eliminate for example, the handwritten annotations from an image. A separation mask is produced that, for example, converts all the image pixels corresponding to machine printed text, and none of the image pixels corresponding to handwritten or handprinted annotations. The separation mask is used in conjunction with the original image to produce separate handwritten annotations and machine printed text images. The invention also provides a method and apparatus for identifying the location of specialized type styles such as bold and italic is disclosed. The method erodes a binary image utilizing structuring elements which provide a relatively large number of hits in regions containing the specialized type styles. The destination image resulting from the erosion is coalesced so as to form masks which may be used to extract portions of the original image containing the specialized type styles.

Segmentation of text styles

Systems and methods for successfully decoding optical images of objects of interest when such objects are situated outside a conventional working range of an imaging system, or when such objects are degraded. The systems and methods are based upon a comparison of computed signals corresponding to distorted images that would be obtained from known objects, such as barcodes, when viewed outside a working range, or when degraded, with actual signals obtained from the object of interest. The computed signals in one embodiment are recorded in a lookup table. An advantage of the systems and methods disclosed is that there results a smooth, monotonic probability of correctly decoding the image of interest, even beyond the working distance. A handheld or portable apparatus useful for practicing the invention is also disclosed.

Synthesis decoding and methods of use thereof

A character recognition system includes a scanner for scanning a character to be processed to produce a character data, which is processed in a predetermined manner to extract a character feature, preferably contour information of the character Preferably, a plurality of predetermined directionality codes each associated with a unique pixel arrangement pattern are prepared and they are assigned to the contour depending on the local pixel arrangement condition The contour information defined by such directionality codes is further processed to define a histogram or feature vector of the directionality codes which is compared with a first group of reference characters without inclination and a second group of reference characters with inclination When a predetermined condition is met, then the mode of operation is switched such that an unknown character is compared with only one of the first and second groups of reference characters

Gen Sato

Papers

Character recognition method and system capable of recognizing slant characters