A new analytic scheme, which uses a sequence of image segmentation and recognition algorithms, is proposed for the off-line cursive handwriting recognition problem. First, some global parameters, such as slant angle, baselines, stroke width and height, are estimated. Second, a segmentation method finds character segmentation paths by combining gray-scale and binary information. Third, a hidden Markov model (HMM) is employed for shape recognition to label and rank the character candidates. For this purpose, a string of codes is extracted from each segment to represent the character candidates. The estimation of feature space parameters is embedded in the HMM training stage together with the estimation of the HMM model parameters. Finally, information from a lexicon and from the HMM ranks is combined in a graph optimization problem for word-level recognition. This method corrects most of the errors produced by the segmentation and HMM ranking stages by maximizing an information measure in an efficient graph search algorithm. The experiments indicate higher recognition rates compared to the available methods reported in the literature.

https://user.ceng.metu.edu.tr/~nafiz/papers/PAMI_2002.pdf

Optical character recognition for cursive handwriting

This paper describes a handwritten character string recognition system for Japanese mail address reading on a very large vocabulary. The address phrases are recognized as a whole because there is no extra space between words. The lexicon contains 111,349 address phrases, which are stored in a trie structure. In recognition, the text line image is matched with the lexicon entries (phrases) to obtain reliable segmentation and retrieve valid address phrases. The paper first introduces some effective techniques for text line image preprocessing and presegmentation. In presegmentation, the text line image is separated into primitive segments by connected component analysis and touching pattern splitting based on contour shape analysis. In lexicon matching, consecutive segments are dynamically combined into candidate character patterns. An accurate character classifier is embedded in lexicon matching to select characters matched with a candidate pattern from a dynamic category set. A beam search strategy is used to control the lexicon matching so as to achieve real-time recognition. In experiments on 3,589 live mail images, the proposed method achieved correct rate of 83.68 percent while the error rate is less than 1 percent.

Lexicon-driven segmentation and recognition of handwritten character strings for Japanese address reading

The system of the present invention allows a user to generate a representation of time-based media. The system of the present invention includes a feature extraction module for extracting features from media content. For example, the feature extraction module can detect solos in a musical performance, or can detect music, applause, speech, and the like. A formatting module formats a media representation generated by the system. The formatting module also applies feature extraction information to the representation, and formats the representation according to a representation specification. In addition, the system can include an augmented output device that generates a media representation based on the feature extraction information and the representation specification. The methods of the present invention include extracting features from media content, and formatting a media representation being generated using the extracted features and based on a specification or data structure specifying the representation format. The methods can also include generating a media representation based on the results of the formatting.

Printable representations for time-based media

A printing system for time-based data enables the printing of time-based media by sharing processing resources on a printer and on an external media processing system such as an external service, for example, a web service. The media processing may similarly be shared, as determined by a resource allocation module, or as indicated by a user via a user interface, between the printer and an external media processing system coupled via a communication interface to the printer or via a network. An example of such an external media processing system is an external device such as a personal computer or an external service such as a web service. A stand-alone version of the printer with embedded time based data in multiple media is described with a display and user interface so that a user can walk up to the printer and perform multimedia processing at the printer. The stand alone version has a network connection or other communication interface so that an external service or device can interface directly with the printer in performing media processing or a user can interface with the external service or device directly through the printer.

Stand alone multimedia printer with user interface for allocating processing

A method, system and computer readable medium for providing for providing a function item, such as a key, button, icon, or menu, tied to a user operation in a computer, whereby a single click on the function item in a window or program on a computer screen, or one single selection in a menu in a program, initiates retrieval of name and addresses and/or other person or company related information, while the user works simultaneously in another program, e.g., a word processor. The click on the function item initiates a program connected to the button to search a database or file available on or through the computer, containing the person, company or address related data, in order to look up data corresponding to what the user types, or partly typed, e.g., name and/or address in the word processor, the correct data from the database, data related to the typed data, e.g., the name of the person, company, or the traditional or electronic address, or other person, or company, or address related data, and alternatively the persons, companies, or addresses, are displayed and possibly entered into the word processor, if such related data exists.

Method, system and computer readable medium for addressing handling from a computer program

The reading of names and addresses is one of the most complex tasks in automated forms processing. This paper describes an integrated real-time system to read names and addresses on tax forms of the U.S. Internal Revenue Service. The Name and Address Block Reader (NABR) system accepts both machine-printed and hand-printed address block images as input. The application software has two major steps: document analysis (connected component analysis, address block extraction, label detection, hand-print/machine-print discrimination) and document recognition. Document recognition has two nonidentical streams for machine-print and hand-print: the key steps are address parsing, character recognition, word recognition, and postal database lookup. (ZIP+4 and City-State-ZIP files.) System output is a packet containing the results of recognition together with database access status file. Real-time throughput (8500 forms/h) is achieved by employing a loosely coupled multiprocessing architecture where successive input images are distributed to available address recognition processors. The functional architecture, software design, system architecture, and the hardware implementation are described. Performance evaluation on machine-printed and handwritten addresses are presented.

A system to read names and addresses on tax forms

The reading of names and addresses is one of the most complex tasks in automated forms processing. The paper describes an integrated real time system to read names and addresses on tax forms of the Internal Revenue Service of the United States. The Name and Address Block Reader (NABR) system accepts both machine printed and hand printed address block images as input. The application software has two major steps: document analysis (connected component analysis, address block extraction, label detection, hand print/machine print discrimination); and document recognition. Document recognition has two non identical streams for machine print and hand print; key steps are: address parsing, character recognition, word recognition and postal database lookup (ZIP+4 and City-State-ZIP files). Real time throughput (8,500 forms per hour) is achieved by employing a loosely coupled multiprocessing architecture. The functional architecture, software design, system architecture and hardware implementation are described. Performance evaluation on machine printed and handwritten addresses are presented.

Name and Address Block Reader system for tax form processing

Commercial forms-reading systems for extraction of data from forms do not meet acceptable accuracy requirements on forms filled out by hand. In December 1993, NIST called industry and research organizations working in the area of handwriting recognition to participate in a test to determine the state of the art in the area. A database of form images containing actual responses received by the US Census Bureau was provided. The handwritten responses are very loosely constrained in terms of writing style, format of response and choice of text. The sizes of the lexicons provided are very large (about 50000 entries) and yet the coverage is incomplete (about 70%). In this paper we discuss the approach taken by CEDAR to automate the task of reading the census forms. The subtasks of field extraction and phrase recognition are described.

Reading handwritten US census forms

This article describes a real-time document image processing system. Its objective is to recognize names and addresses from scanned address block images extracted from various tax forms of the United States Internal Revenue Service. The Name and Address Block Reader (NABR) system accepts both machine- and hand-printed address block images as input. Salient aspects of the system are presented, including document analysis (connected component analysis, address block extraction, label detection, hand-print/machine-print discrimination) and document recognition. Document recognition is performed in two nonidentical streams for machine-and hand-print; key steps are address parsing, character recognition, word recognition, and postal data base lookup (ZIP+4 and city-state-ZIP files). System output is a packet containing the results of recognition together with data base access status file. Real-time throughput (8500 forms/h) is achieved by employing a loosely coupled multiprocessing architecture where successive input images are distributed to available address recognition processors. The functional architecture, software design, system architecture, and the hardware implementation are described. Performance evaluation on machine- and hand-written addresses are presented. © 1996 John Wiley & Sons, Inc.

Document image-processing system for name and address recognition

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A system to read names and addresses on tax forms

Name and Address Block Reader system for tax form processing

Reading handwritten US census forms

Document image-processing system for name and address recognition

Document image-processing system for name and address recognition