AN IMPROVED STRUCTURAL APPROACH FOR AUTOMATED RECOGNITION OF HANDPRINTED CHARACTERS

1991 ◽  
Vol 05 (01n02) ◽  
pp. 97-121 ◽  
Author(s):  
PATRICK SHEN-PEI WANG ◽  
AMAR GUPTA
Keyword(s):  
Pattern Recognition ◽  
Real Time ◽  
Character Recognition ◽  
Line Drawing ◽  
Lower Degree ◽  
Automated Recognition ◽  
Chain Code ◽  
Pattern Recognition Methods ◽  
On Line ◽  
Descriptive Language

This paper examines several line-drawing pattern recognition methods for handwritten character recognition. They are the picture descriptive language (PDL), Berthod and Maroy (BM), extended Freeman's chain code (EFC), error transformation (ET), tree grammar (TG), and array grammar (AG) methods. A new character recognition scheme that uses improved extended octal codes as primitives is introduced. This scheme offers the advantages of handling flexible sizes, orientations, and variations, the need for fewer learning samples, and lower degree of ambiguity. Finally, the simulation of off-line character recognition by the real-time on-line counterpart is investigated.

A STRUCTURAL APPROACH TO ON-LINE CHARACTER RECOGNITION: SYSTEM DESIGN AND APPLICATIONS

1991 ◽  
Vol 05 (01n02) ◽  
pp. 311-335 ◽  
Author(s):  
FATHALLAH NOUBOUD ◽  
RÉJEAN PLAMONDON
Keyword(s):  
Character Recognition ◽  
Computation Time ◽  
Experimental Tests ◽  
Recognition System ◽  
Structural Approach ◽  
Chain Code ◽  
String Comparison ◽  
Average Computation Time ◽  
On Line ◽  
A Chain

This paper presents a real-time constraint-free handprinted character recognition system based on a structural approach. After the preprocessing operation, a chain code is extracted to represent the character. The classification is based on the use of a processor dedicated to string comparison. The average computation time to recognize a character is about 0.07 seconds. During the learning step, the user can define any set of characters or symbols to be recognized by the system. Thus there are no constraints on the handprinting. The experimental tests show a high degree of accuracy (96%) for writer-dependent applications. Comparisons with other system and methods are discussed. We also present a comparison between the processor used in this system and the Wagner and Fischer algorithm. Finally, we describe some applications of the system.

Monitoring the wheat straw fermentation process using an electronic nose with pattern recognition methods

2015 ◽  
Vol 7 (14) ◽  
pp. 6006-6011 ◽  
Author(s):  
Congli Mei ◽  
Ming Yang ◽  
Dongxin Shu ◽  
Hui Jiang ◽  
Guohai Liu
Keyword(s):  
Pattern Recognition ◽  
Solid State ◽  
Wheat Straw ◽  
Real Time ◽  
Electronic Nose ◽  
Solid State Fermentation ◽  
Fermentation Process ◽  
Pattern Recognition Methods

To monitor the wheat straw solid-state fermentation process in real time, an electronic nose (e-nose) was attempted in this study.

Real-time on-line pattern recognition of eye position and movement

1985 ◽  
Vol 132 (6) ◽  
pp. 293
Author(s):  
H.F. Li ◽  
F.H.Y. Chan ◽  
P.W.F. Poon ◽  
W.F. Yan ◽  
W.Y. Wong ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Real Time ◽  
Eye Position ◽  
Line Pattern ◽  
On Line

APPLICATIONS OF NEURAL NETWORKS TO CHARACTER RECOGNITION

1991 ◽  
Vol 05 (01n02) ◽  
pp. 353-382 ◽  
Author(s):  
I. GUYON
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Pattern Recognition ◽  
Character Recognition ◽  
Expert Knowledge ◽  
Learning Algorithms ◽  
Network Architectures ◽  
General Introduction ◽  
On Line ◽  
The Many

Among the many applications that have been proposed for neural networks, character recognition has been one of the most successful. Compared to other methods used in pattern recognition, the advantage of neural networks is that they offer a lot of flexibility to the designer, i.e. expert knowledge can be introduced into the architecture to reduce the number of parameters determined by training by examples. In this paper, a general introduction to neural network architectures and learning algorithms commonly used for pattern recognition problems is given. The design of a neural network character recognizer for on-line recognition of handwritten characters is then described in detail.

scholarly journals Pattern Recognition Of Javanese Letter Using Template Matching Correlation Method

2018 ◽  
Vol 3 (2) ◽  
pp. 49-56
Author(s):  
Irham Ferdiansyah Katili ◽  
Fairuz Dyah Esabella ◽  
Ardytha Luthfiarta
Keyword(s):  
Pattern Recognition ◽  
Character Recognition ◽  
Template Matching ◽  
Optical Character Recognition ◽  
Correlation Method ◽  
Pattern Recognition Methods ◽  
Java Language ◽  
Modern Age ◽  
Template Image ◽  
The Impact

In this modern age, the impact of globalization is increasingly entering and expanding into most societies. One impact of globalization makes people prefer to learn the language and use a foreign language rather than the local language, especially the Java language. It is very influential on the knowledge of the community about the existence or the existence of Javanese Letter, especially in the field of education. In this study, In this research will be made an application to recognize the writing of Javanese Letter based on Optical Character Recognition (OCR). Matching templates correlation can be used as pattern recognition methods. How the Template Matching Algorithm works by matching the template image with the test image after going through the Pre-processing and segmentation process. From the research that has been done by using 10 character template and 20 data testing get accuracy equal to 93.44% and error rate 6.56%. So the Matching Template Algorithm can well recognize the Javanese Letter pattern.

APPLICATION OF GUARDED FUZZY-ATTRIBUTE CONTEXT FREE GRAMMAR TO SYNTACTIC PATTERN RECOGNITION

1992 ◽  
Vol 06 (05) ◽  
pp. 777-797 ◽  
Author(s):  
KWOK-PING CHAN
Keyword(s):  
Pattern Recognition ◽  
Character Recognition ◽  
Concurrent Programming ◽  
High Dimensional ◽  
Simple Scheme ◽  
Simple Modification ◽  
Context Free Grammar ◽  
Syntactic Pattern ◽  
On Line ◽  
Context Free

High-dimensional grammars such as web grammars and plex grammars were used in syntactic recognition of complex 2-D or 3-D objects. In this paper, we present a simple modification, borrowing the concept of guards from concurrent programming to attributed grammar proposed by D. E. Knuth. We show that the resultant grammar can handle patterns described by the high-dimensional grammars. The only problem is that we may not have a simple ordering of the terminal symbols or pattern primitives. In some applications, such as on-line character recognition, the problem does not exist and hence presents a good candidate for the application. We also discuss the incorporation of fuzzy attributes and the necessary modification is hence introduced. Finally, the error transformations proposed by K. S. Fu can easily be taken into consideration and a powerful yet simple scheme presented.

Software pattern recognition applied to nanodiffraction patterns from a STEM instrument

1986 ◽  
Vol 44 ◽  
pp. 694-695
Author(s):  
G.Y. Fan ◽  
J.M. Cowley
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Computer Software ◽  
Processing System ◽  
Light Level ◽  
Host Computer ◽  
Low Light ◽  
Image Processing System ◽  
Recent Developments ◽  
On Line

In recent developments, the ASU HB5 has been modified so that the timing, positioning, and scanning of the finely focused electron probe can be entirely controlled by a host computer. This made the asynchronized handshake possible between the HB5 STEM and the image processing system which consists of host computer (PDP 11/34), DeAnza image processor (IP 5000) which is interfaced with a low-light level TV camera, array processor (AP 400) and various peripheral devices. This greatly facilitates the pattern recognition technique initiated by Monosmith and Cowley. Software called NANHB5 is under development which, instead of employing a set of photo-diodes to detect strong spots on a TV screen, uses various software techniques including on-line fast Fourier transform (FFT) to recognize patterns of greater complexity, taking advantage of the sophistication of our image processing system and the flexibility of computer software.

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