Topic
Intelligent word recognition
About: Intelligent word recognition is a research topic. Over the lifetime, 2480 publications have been published within this topic receiving 45813 citations.
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TL;DR: Several recognition algorithms used in the interpretation of handwritten and machine-printed address text (digits/symbols/alphabets/words) are described.
147 citations
20 Oct 1993
TL;DR: In this paper, a lexicon directed algorithm for recognition of unconstrained handwritten words (cursive, discrete, or mixed) such as those encountered in mail pieces is described.
Abstract: Discusses improvements made to a lexicon directed algorithm for recognition of unconstrained handwritten words (cursive, discrete, or mixed) such as those encountered in mail pieces. The procedure consists of binarization, pre-segmentation, intermediate feature extraction, segmentation recognition, and post-processing. The segmentation recognition and the post-processing are repeated for all lexicon words while the binarization to the intermediate feature extraction are applied once for an input word. The result of performance evaluation using large handwritten address block database is described, and algorithm improvements are described and discussed, in order to achieve higher recognition accuracy and speed. As a result the performance for lexicons of size 10, 100, and 1000 are improved to 98.01%, 95.46%, and 91.49% respectively. The processing speed for each lexicon is improved to 2.0, 2.5, and 3.5 sec/word on a SUN SPARC station 2. >
144 citations
TL;DR: In this paper, the authors described techniques to separate a line of unconstrained (written in a natural manner) handwritten text into words, using original algorithms to determine distances between components in a text line and to detect punctuation.
142 citations
TL;DR: This paper presents a new method on off-line recognition of handwritten Arabic script that does not require segmentation into characters, and is applied to cursive Arabic script, where ligatures, overlaps and style variation pose challenges to the recognition system.
134 citations
03 Aug 2003
TL;DR: An automatic scheme is presented to identify text lines of different Indian scripts from a document with an overall accuracy of about 97.52% based on water reservoir principle, contour tracing, profileetc.
Abstract: A document page may contain two or more different scripts.For Optical Character Recognition (OCR) of such adocument page, it is necessary to separate different scriptsbefore feeding them to their individual OCR system. In thispaper an automatic scheme is presented to identify text linesof different Indian scripts from a document. For theseparation task at first the scripts are grouped into a fewclasses according to script characteristics. Next featurebased on water reservoir principle, contour tracing, profileetc. are employed to identify them without any expensiveOCR-like algorithms. At present, the system has an overallaccuracy of about 97.52%.
133 citations