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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16 Sep 1996
TL;DR: This work presents a novel algorithm for automatic written language recognition based on texture analysis, where each language is regarded as a different texture in order to apply any standard texture recognition algorithm for the task.
Abstract: Numerous techniques have been reported for optical character recognition (OCR). Almost all such techniques make an implicit assumption that the language of the document to be processed is known. We attempt to eliminate this assumption by presenting a novel algorithm for automatic written language recognition. Given that different languages are often visually distinctive in written form, we take a global approach based on texture analysis, where each language is regarded as a different texture. In principle this allows us to apply any standard texture recognition algorithm for the task. Experiments with six languages clearly demonstrate the great potential of the proposed global approach.
31 citations
20 Sep 1999
TL;DR: The proposed method extracts reliable high-intensity regions in a video text region and then expands them in order to make the whole video character regions to be superior to the conventional methods.
Abstract: The paper presents a method to precisely extract only video character portions from a video text rectangle region in order to make a readable image for OCR. In conventional methods, gray image binarization processing with a given threshold is employed to extract high-intensity video character regions. A video has a complex background with various kinds of intensity so that appropriate thresholds are not always obtained. The proposed method extracts reliable high-intensity regions in a video text region and then expands them in order to make the whole video character regions. The experiments show this new method to be superior to the conventional methods.
31 citations
Patent•
05 Jun 1991
TL;DR: A character recognition system for orientation independence, position independence, and orientation and position independence is described in this article.The system also provides a technique for implementing concurrency in the processing without sacrificing performance.
Abstract: A character recognition system wherein the flexibility of the recognition task is expanded for orientation independence, position independence, and orientation and position independence. The system also provides a technique for implementing concurrency in the processing to achieve high speed without sacrificing performance. The system is readily implemented on conventional machine vision computing systems.
31 citations
TL;DR: An artificial neural network-based OCR algorithm for ANPR application and its efficient architecture are presented and it is shown that the proposed architecture can meet the real-time requirement of an ANPR system and can process a character image in 0.7 ms with 97% successful character recognition rate.
Abstract: The last main stage in an automatic number plate recognition system (ANPRs) is optical character recognition (OCR), where the number plate characters on the number plate image are converted into encoded texts. In this study, an artificial neural network-based OCR algorithm for ANPR application and its efficient architecture are presented. The proposed architecture has been successfully implemented and tested using the Mentor Graphics RC240 field programmable gate arrays (FPGA) development board equipped with a 4M Gates Xilinx Virtex-4 LX40. A database of 3570 UK binary character images have been used for testing the performance of the proposed architecture. Results achieved have shown that the proposed architecture can meet the real-time requirement of an ANPR system and can process a character image in 0.7 ms with 97.3% successful character recognition rate and consumes only 23% of the available area in the used FPGA.
31 citations
18 Aug 1997
TL;DR: This paper describes a real-time system intended to recognize the 5-digit ZIP code part of DPC and the main principles of the handwritten word recognizer which provide the core of the system are explained.
Abstract: The encoding of delivery point code (DPC) for a handwritten address is one of the most complex problems of the US mail delivery automation. This paper describes a real-time system intended to recognize the 5-digit ZIP code part of DPC. To increase the system performance the results of ZIP code recognition are cross-validated with those of city and state name recognition. The main principles of the handwritten word recognizer which provide the core of the system are explained. The system throughput is 40,000 address blocks per hour. Experimental results on live mail pieces are presented. The ZIP code recognition rate is 73% with 1% error rate.
31 citations