Showing papers on "Optical character recognition published in 1976"

Optical recognition system

Abstract: Described is an optical character recognition system wherein total data entry is accomplished through a hand held unit. The unit includes an optical scanner, a keyboard and a display which communicate with a portable character recognition unit.

Character reading techniques

Abstract: A remote optical character recognition system including a central processor time-shared among a number of remote scanner units each adapted to receive a document bearing information characters to be scanned so as to produce corresponding signals which are transmitted to the central processor for analysis, whereby signals are developed identifying each of the information characters on the document. The document is additionally provided with control characters presented with a distinctive characteristic to enable the central processor to distinguish the control characters from the information characters. The central processor identifies the control characters and produces corresponding control effects related to procedures for scanning the document and processing the scan data. Certain of the control characters provide basic information concerning the particular customer whose document is being scanned, as well as initial instructions such as specifying portions of the document to be scanned. Other control characters relate specifically to corresponding information characters placed in directly associated data fields on the document.

Optical character recognition system

Abstract: An optical character recognition system for identifying typewritten characters and converting such to standard code for transmission. To achieve recognition of a character, the character, as it is scanned, is recorded in a corresponding array in memory and the memory address for each scan coordinate is then modified to correspond with the virtual character center. This coordinate center of the character is derived by inspection of the scanning array in parallel with the memory storing pass to determine the two adjacent all white rows and columns bounding the character. The coordinate center is then calculated by dividing the bounded row and column increment by two. The recognition of the character pattern is then performed by a set of Boolean discriminants selected to achieve the highest probability of in - character hits against a lowest probability of misses. Print fidelity, quantum misregistration and other character edge noise are filtered by selective OR-ing of test points along an axis having the highest incidence of noise.

Optical character recognition system

Abstract: An optical character recognition system wherein both feature analysis and matrix analysis operations are performed to insure proper identification of a character under scan. Operating speed and reliability are enhanced by initially classifying the character under scan as being included in a first sub-group of characters having features in common with the character being scanned whereafter final indentification of the unknown character from among the selected sub-group is effected by means of a comparison operation based on a weighted matrix analysis. Preprocessing steps are taken to precisely frame the informational content of the character under scan. The preprocessing steps are effected as the information defining the character is being digitized. Simultaneously therewith the digital information is temporarily stored and, upon completion of the character framing operation, the temporarily stored information is gated into a random access memory (RAM) for use in the further processing operations.

Automated character recognition system

Abstract: A reliable optical character recognition system substantially insensitive to variations in character stroke size is provided for reading numeric and special characters printed on a document surface in plural fonts of unknown order. More particularly, a character is scanned and its image stored in a two-dimensional mosaic without requiring precise positioning therein, amplitude correlation for video signal quantization, or normalization of character stroke sizes. The image mosaic is scanned by a row-column analyzer to detect primary features of the image including the number of character segments in the rows and columns, the segment length and rightmost segment coordinate for those rows containing only a single segment, and the segment length for those columns having a single segment. Feature decision logic analyzes the primary features to form a set of secondary features based upon the occurrence and order of the primary features. The set of secondary features then are analyzed in a sequential logic decision tree to identify the character.