Topic
Optical character recognition
About: Optical character recognition is a research topic. Over the lifetime, 7342 publications have been published within this topic receiving 158193 citations. The topic is also known as: OCR & optical character reader.
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TL;DR: Experimental results demonstrate the utility of the Choquet fuzzy integral in handwritten word recognition and indicate a simple choice of fuzzy integral works better than a more complex choice.
Abstract: The Choquet fuzzy integral is applied to handwritten
word recognition. A handwritten word recognition system is described. The word recognition system assigns a recognition confidence value to each string in a lexicon of candidate strings. The system uses a lexicon-driven approach that integrates segmentation and recognition via dynamic programming matching. The dynamic programming matcher finds a segmentation of the word image for each string in the lexicon. The traditional match score between a segmentation and a string is an average. In this paper, fuzzy integrals are used instead of an average. Experimental results demonstrate the utility of this approach. A surprising result is obtained that indicates a simple choice of fuzzy integral works better than a more complex choice.
35 citations
11 Aug 2002
TL;DR: Two innovative techniques that contribute to the high efficiency in recognition of the mixed Chinese/English text line are presented, including a progressive search strategy based on character verification and a tree-based fast match technique with a confidence-guided adaptive stopping mechanism.
Abstract: In the past several years, we have been developing a high performance OCR engine for machine printed Chinese/English documents. We present two innovative techniques that contribute to the high efficiency in recognition of the mixed Chinese/English text line. They are (1) a progressive search strategy based on character verification, and (2) a tree-based fast match technique with a confidence-guided adaptive stopping mechanism. The efficacy of the proposed techniques is confirmed by experiments in a benchmark test.
35 citations
Book•
01 Jan 1980TL;DR: Reading is a need and a hobby at once and this condition is the on that will make you feel that you must read.
Abstract: Some people may be laughing when looking at you reading in your spare time. Some may be admired of you. And some may want be like you who have reading hobby. What about your own feel? Have you felt right? Reading is a need and a hobby at once. This condition is the on that will make you feel that you must read. If you know are looking for the book enPDFd computer programs for spelling correction an experiment in program design as the choice of reading, you can find here.
35 citations
30 Mar 1995
TL;DR: This paper presents a preliminary report on the design and evaluation of a system to automatically markup technical documents, based on information provided by an OCR device that differs from traditional OCR devices in that it not only performs optical character recognition, but also provides detailed information about page layout, word geometry, and font usage.
Abstract: One predominant application of OCR is the recognition of full text documents for information retrieval. Modern retrieval systems exploit both the textual content of the document as well as its structure. The relationship between textual content and character accuracy have been the focus of recent studies. It has been shown that due to the redundancies in text, average precision and recall is not heavily affected by OCR character errors. What is not fully known is to what extent OCR devices can provide reliable information that can be used to capture the structure of the document. In this paper, we present a preliminary report on the design and evaluation of a system to automatically markup technical documents, based on information provided by an OCR device. The device we use differs from traditional OCR devices in that it not only performs optical character recognition, but also provides detailed information about page layout, word geometry, and font usage. Our automatic markup program, which we call Autotag, uses this information, combined with dictionary lookup and content analysis, to identify structural components of the text. These include the document title, author information, abstract, sections, section titles, paragraphs, sentences, and de-hyphenated words. A visual examination of the hardcopy is compared to the output of our markup system to determine its correctness.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
35 citations
TL;DR: A segmentation-free optical character recognition system for printed Urdu Nastaliq font using ligatures as units of recognition using Hidden Markov Models for classification is presented.
Abstract: This paper presents a segmentation-free optical character recognition system for printed Urdu Nastaliq font using ligatures as units of recognition. The proposed technique relies on statistical features and employs Hidden Markov Models for classification. A total of 1525 unique high-frequency Urdu ligatures from the standard Urdu Printed Text Images (UPTI) database are considered in our study. Ligatures extracted from text lines are first split into primary (main body) and secondary (dots and diacritics) ligatures and multiple instances of the same ligature are grouped into clusters using a sequential clustering algorithm. Hidden Markov Models are trained separately for each ligature using the examples in the respective cluster by sliding right-to-left the overlapped windows and extracting a set of statistical features. Given the query text, the primary and secondary ligatures are separately recognized and later associated together using a set of heuristics to recognize the complete ligature. The system evaluated on the standard UPTI Urdu database reported a ligature recognition rate of 92% on more than 6000 query ligatures.
35 citations