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Optical character recognition

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	Optical character recognition - Wikipedia, the free encyclopedia
		Optical character recognition, usually abbreviated to OCR, is computer software designed to translate images of handwritten or typewritten text (usually captured by a scanner) into machine-editable text, or to translate pictures of characters into a standard encoding scheme representing them (e.g.
		Optical character recognition (using optical techniques such as mirrors and lenses) and digital character recognition (using scanners and computer algorithms) were originally considered separate fields.
		Early research into recognition of printed sheet music was performed in the mid 1970s at MIT and other institutions.
	en.wikipedia.org /wiki/Optical_character_recognition (1683 words)

	Optical character recognition Summary
		However, though the characters are recognized in a way that allows most words and even sentences to appear correctly in the generated file, a significant limitation is that most OCR software today does not correctly recognize footnotes, page numbers, marginal comments, headers, italicized text, and the like.
		Character recognition is the technology of using machines to identify symbols (usually alphanumeric characters) in order to express them as machine readable codes.
		Computer pattern recognition developed as a specialized form of character recognition and is used by manufacturers who utilize industrial robots.
	www.bookrags.com /Optical_character_recognition (3723 words)

	Character Recognition by Feature Point Extraction
		Its recognition rate is currently not as high as the recognition rates of the older, more developed character recognition algorithms, but it is expected that if it were expanded to work with a larger set of features this problem would be removed.
		The output for each set run against the reference consisted of ASCII output showing the shape of the character (with the feature points marked), the name of the closest match, the distance from that closest match, and the name of the character if identification was possible.
		Characters could also be displayed from the dictionary from a menu prompt to make visual comparison of the assorted characters in the test sets and the dictionary characters possible (see Figure 1, "Character Display,").
	www.ccs.neu.edu /home/feneric/charrec.html (3443 words)

	OCR Technologies \| Printed Character Recognition (PCR)
		In practice, a font character to be recognized is often unknown a priori.
		Thus, the problem of characters separation is reduced to a problem of correct partition of an ordered sequence of atoms.
		The average value of the recognition probabilities obtained for the corresponding molecules provides an estimate of the confidence of the entire word.
	www.research.ibm.com /haifa/projects/image/ocr/pcr.html (509 words)

	OCR - Optical Character Recognition
		Optical character recognition; the act of using a visual scanning device to read text from hard copy and translate it into a format a computer can access (e.g., an ASCII file).
		Optical Character Recognition is a visual recognition process that turns printed or written text into an electronic character based file.
		Optical character recognition is a technology which takes data from a paper document and turns it editable text data.
	www.auditmypc.com /acronym/OCR.asp (765 words)

	Plate Recognition
		A typical LPI/R system is comprised of a video image-acquisition subsystem, a CPU for image processing and control, a hardware- or software-based character recognition engine, and a storage or transmission subsystem for electronically recording plate contents and data such as date, time, and location.
		Buyers should distinguish between absolute identification of each and every character, as for a traffic violation application-- an example that requires doing so accurately and reproducibly-- versus recognizing a plate that the system has seen before; as in inventory control where the universe of plates is finite and known.
		Following the recognition step, each plate's sequence of characters is submitted for matching against a database of known sets.
	www.photocop.com /recognition.htm (2398 words)

	Humanities Computing
		Characters are recognized and discriminated according to how much they participate in the "letter-ness" of any particular Form of letter.
		In visual terms, a word is distinguished by its characters' relation to the white space surrounding it and the nature of its letter face (for instance, small thin strokes are common to handwriting, and thick short strokes are common to non-serifed print fonts).
		Standing as we are at the beginning of the Digital Age, computer Optical Character Recognition would seem to be one of those key processes that make the important leap from the world of print which we have known for centuries to the newly charted realm of digital documents.
	www.nyu.edu /its/pubs/connect/archives/99spring/killingsocr.html (1550 words)

	LGR - OPTICAL CHARACTER RECOGNITION
		Continuing this work toward handwriting recognition, Earnest has developed a set of simple tests on the strokes in a word, which enables a computer to pick likely words from a dictionary [6].
		Another type of character input that is being considered at M.I. T.is an "electronic drafting board" intended for real-time multisequence computer usage.
		Since the sequence of points is also known by the computer, character recognition is simpler.
	www.packet.cc /files/recent-development.html (1102 words)

	Character recognition - Ways to convert business documents into electronic format (Site not responding. Last check: 2007-10-09)
		Character recognition is the foundation of OCR, (Optical Character Recognition).
		Character recognition allows automatic data capture software or optical imaging software to recognize characters by analyzing pixel-based patterns in images such as scanned paper documents or electronic fax files.
		Accurate character recognition is an important cornerstone in the procedure, transforming the document images into actual editable text.
	www.readsoft.net /character-recognition.shtml (139 words)

	Optical Character Recognition
		Neural networks are often used in OCR applications for the character recognition task and have been shown to greatly improve the translation accuracy over less sophisticated methods.
		If the network can only recognize character images that exactly match the ones in the training set, the model would not be useful in an OCR application that must process many different and imperfect character images.
		To build a character recognition model for a full-featured OCR application, the neural net model must be significantly more sophisticated than our sample shown here.
	www.qnetv2k.com /Qnet2000Manual/html/qnet65ym.htm (852 words)

	Handwriting recognition - Wikipedia, the free encyclopedia
		The image of the written text may be sensed "off line" from a piece of paper by optical scanning (optical character recognition).
		On-line handwriting recognition involves the automatic conversion of text as it is written on a special digitizer or PDA, where a sensor picks up the pen-tip movements X(t),Y(t) as well as pen-up/pen-down switching.
		By the time of the release of the Newton OS 2.0, wherein the handwriting recognition was greatly improved, including unique features still not found in current recognition systems such as modeless error correction, the largely negative first impression had been made.
	en.wikipedia.org /wiki/Handwriting_recognition (709 words)

	Character Recognition Techniques - A Demo Program (Site not responding. Last check: 2007-10-09)
		Greater accuracy in character recognition can also be obtained by carefully matching the scanned image font with the installed fonts in the system.
		Accuracy of recognition greatly depends upon the typeface of the font and the font size.
		For instance to separate two characters, which are joined in the middle, a simple scanning of the character from the right boundary to left could be carried out.
	www.infitt.org /minmanjari/issue1_1/vasudevan.html (2785 words)

	Character Recognition Overview
		The comparison algorithm is simple: it sums the squares of the differences between each property in the extracted character and each property in the learned character, returning a "Confidence".
		Initially, we compared each extracted character to the entire linked list of learned characters, but in the interest of speed, we modified this slightly to classify characters in relation to the baseline of their line of text.
		Because we found that some characters made it past the original character recognition algorithm, we deemed it necessary to perform additional operations on poorly recognized characters.
	http.cs.berkeley.edu /~fateman/kathey/char_recognition.html (873 words)

	Character Recognition
		The variables that affect the performance of an optical character recognition (OCR) system include variations in the clarity of printed documents, as well as their layout style.
		To objectively measure progress in character recognition technology and to identify research problems, two kinds of evaluation are needed: internal evaluation and independent evaluation.
		Since character recognition systems can be customized or trained to accurately recognize a given set of data, independent evaluation is also required for objective final assessment.
	cslu.cse.ogi.edu /HLTsurvey/ch13node12.html (1254 words)

	Applying Neural Networks to Character Recognition
		The rationale is that when the algorithm does misclassify a character (as every algorithm does) it should pick a character that a human would consider to be a reasonable guess, because it is easier for humans to correct mistakes that are typical of humans (i.e.
		Comparisons were executed by computing the sum of the minimum distances between the feature points of the character to be identified and the feature points of the dictionary character.
		It was made to train on the same character set that the feature extraction algorithm had used as its dictionary (see Figure 3, "The CBM Character Set and Extracted Feature Points").
	www.ccs.neu.edu /home/feneric/charrecnn.html (1616 words)

	Character Recognition
		Character recognition fonts are divided in two groups, Magnetic Ink Character Recognition (MICR) and Optical Character Recognition (OCR).
		By the end of the sixties the time was ripe for full character recognition.
		The first standardized character set had the digits and letters, plus a few more letters with diacritical signs for other western languages.
	homepages.cwi.nl /~dik/english/codes/charrec.html (792 words)

	OCR \| Optical Character Recognition
		When a character is recognized, it is then converted into an ASCII code.
		characters are broken or not properly printed, OCR typically fails to recognize the text.
		The character sets of certain languages might not be supported.
	www.ilixis.com /developer/recognition.html (489 words)

	Character recognition system (US5347593)
		An arrangement for acquiring signal representatives intended to correspond to character representations, out of a set of possible character representations, provided on a substrate that emanate magnetic fields which can be sensed to provide a related waveform.
		Times of extrema of the waveform are ordered and compared with the ordering of time locations in waveforms expected for the set of possible characters with different orderings being used to eliminate those possible characters having expected waveforms incompatible with the extrema ordered times of the measured waveform.
		A method for acquiring signal representations intended to correspond to those character representations, out of a set of possible known character representations, provided on a nonmagnetic material substrate so as to be capable of establishing corresponding magnetic fields, said method comprising:
	www.delphion.com /details?pn10=US05347593 (304 words)

	OCR Systems
		Although not originally developed for users who are visually impaired, Optical Character Recognition (OCR) technology has become an aid for inputting documents quickly by and for users with vision impairments.
		Then, during the recognition process, the picture is analyzed for layout, fonts, text and graphics.
		The OpenBook is an optical character recognition system which converts text pages into an electronic text file and reads them with a voice synthesizer.
	www2.edc.org /NCIP/library/vi/ocr.htm (1199 words)

	Project Report by Asha and Pooja
		Thus, we created a partial thinning algorithm which finds out the average width of the characters in the image and if this width is more than 3, the partial thinning algorithm thins all the characters depending on their width.
		If the directions match, the character corresponding to this feature-graph is added to the possibility and the Continuous Matching algorithm is called recursively with the rest of the features.
		Characters: Depending on the relative position of features in it, a character can be viewed as a Directional Graph of Features called feature-graphs.
	www.cse.iitk.ac.in /~amit/courses/768/00/asha (3453 words)

	OCR Software, Optical Character Recognition for Production Data Capture
		Taskmaster Recognition capabilities include barcode recognition to read regular barcodes (Code 39, 2 of 5 Interleaved, CodaBar, etc.) and high-density, two dimensional (2D) barcodes, including PDF-417.
		Taskmaster Optical Mark Recognition (OMR) reads check boxes, bubbles or other shapes that have been filled in by hand is a great way of getting accurate data fast.
		Taskmaster Recognition Tasks use two OCR or ICR recognition "engines," and can compare and contrast, or "vote", on the accuracy value to assign to any character and select the best candidate between them.
	www.datacap.com /products/features/recog (355 words)

	optical character recognition
		First, a scanner produces a digital image of the text; then character-recognition software makes use of stored knowledge about the shapes of individual characters to convert the digital image to a set of internal codes that can be stored and processed by a computer.
		OCR originally required specially designed characters but current devices can recognize most standard typefaces and even handwriting.
		OCR is used, for example, by gas and electricity companies to input data collected on meter-reading cards, and by personal digital assistants to recognize users' handwriting.
	www.tiscali.co.uk /reference/encyclopaedia/hutchinson/m0034373.html (277 words)

	The Pattern Recognition Basis of AI
		and feed it into the pattern recognition algorithm of your choice, the nearest neighbor algorithm is easy or backprop is very popular.
		To get effective pattern recognition without this technique you would have to list large numbers of vectors, one for each possible way of drawing the E within the 21 x 21 area.
		A more complicated version is the Ledeen character recognition algorithm found in Principles of Interactive Computer Graphics by Newman and Sproull, McGraw-Hill, 1973.) In general you don't necessarily want the 9 small squares I've used, other areas of different sizes and shapes may work better.
	www.dontveter.com /basisofai/char.html (1036 words)

	Optical Character Recognition - Test for Unicode support in Web browsers
		The characters that appear in the first column of the following table depend on the browser that you are using, the fonts installed on your computer, and the browser options you have chosen that determine the fonts used to display particular character sets, encodings or languages.
		To see exactly which characters are included in a particular font, you can use a utility such as Andrew West’s BabelMap, or WunderMoosen’s FontChecker.
		The hexadecimal numbers and the character names in the above table are taken from the Unicode 3.0 Character Database, Copyright © 1991-1999 Unicode, Inc., as contained in UnicodeData-Latest.txt on the Unicode ftp site (ftp://ftp.unicode.org/Public/UNIDATA/) in October 1999.
	www.alanwood.net /unicode/optical_character_recognition.html (188 words)

	EzData intelligent character recognition software and form processing.
		EzData™ can help your company cut costly overhead by using intelligent character recognition to reducing the amount of time to get your paper forms into a database.
		EzData™ is the best low cost solution for intelligent character recognition (ICR), (OCR) optical character recognition, object mark recognition (OMR), and bar-code form processing.
		At the push of a button our highly accurate handprint character recognition engines will automatically process your forms, create a database for you, and store the data in the database after you have verified the accuracy.
	www.creativeicr.com (418 words)

	GOCR (via CobWeb/3.1 planetlab2.tamu.edu) (Site not responding. Last check: 2007-10-09)
		GOCR is an OCR (Optical Character Recognition) program, developed under the GNU Public License.
		During that time some characters will be recognized by the new engine, whereas the rest is still recognized by the old engine.
		The number of characters handled by the new engine will increase stepwise in the next releases, so dont wonder if old solved problems appear again.
	jocr.sourceforge.net.cob-web.org:8888 (436 words)

	Optical Character Recognition Systems - American Foundation for the Blind (Site not responding. Last check: 2007-10-09)
		Optical character recognition (OCR) technology offers blind and visually impaired persons the capacity to scan printed text and then speak it back in synthetic speech or save it to a computer.
		The recognition process takes account of the logical structure of the language.
		An OCR system will deduce that the word "tke" at the beginning of a sentence is a mistake and should be read as the word "the." OCR's also use a lexicon and apply spell checking techniques similar to those found in many word processors.
	www.afb.org /info_document_view.asp?documentid=1283 (719 words)

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