• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.10
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• pp.1347-1357
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• 1995

In this paper, we describe a modularized neuroclassifier for enhancing the recognition accuracy of mixed printed and handwritten numerals. This classifier combines four modularized subclassifiers using multi-layer perceptron module. The input of each subclassifier is comprised of a group of specialized feature sets. On applying this method to combining several subclassifiers for unconstrained handwritten numerals, the experimental result shows that the performance of individual subclassifier can be improved. In winner-take-all voting method, the result of subclassifier having the highest RF value is selected as the output. The generality of this classifier is tested with 1,080 printed and 3,000 handwritten numerals that was not shown in training the neural networks. Experimental results show 98.2% recognition rate. The typical recognition test with a threshold value(RF=1.5) has shown 97% recognition, 1% substitution and 2% rejection rates.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1301-1304
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• 1998

Several neural networks have been successfully used to classify complex patterns such as handwritten numerals or words. This paper describes the discrimination of totally unconstrained handwritten numerals using the proposed chaotic neural network (CNN) to improve the recognition rate. The recognition system in the paper consists of the preprocessing stage to extract features using Kirsch mask and the classification stage to recognize numerals using the CNN. In order to evaluate the performance of the proposed network, we performed the recognition with unconstrained handwritten numeral database of Concordia university, Canada. Experimental results show that the CNN based recognizer performs higher recognition rate than other neural network-based methods reported using same database.

• Journal of the Korea Society of Computer and Information
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• v.14 no.8
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• pp.65-71
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• 2009

Natural language processing is necessary in order to efficiently perform filtering tremendous information produced in information retrieval of world wide web. This paper suggested an algorithm for meaning of numerals in the text. The algorithm for meaning of numerals utilized context-free grammars with the chart parsing technique, interpreted affixes connected with the numerals and was designed to disambiguate their meanings systematically supported by the n-gram based words. And the algorithm was designed to use POS (part-of-speech) taggers, to automatically recognize restriction conditions of trigram words, and to gradually disambiguate the meaning of the numerals. This research performed experiment for the suggested system of the numeral interpretation. The result showed that the frequency-proportional method recognized the numerals with 86.3% accuracy and the condition-proportional method with 82.8% accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1031-1033
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• 2005

This paper presents a system of handwritten numerals recognition, which is based on Ant-miner algorithm (data mining based on Ant colony optimization). At the beginning, three distinct fractures (also called attributes) of each numeral are extracted. The attributes are Loop zones, End points, and Feature codes. After these data are extracted, the attributes are in the form of attribute = value (eg. End point10 = true). The extraction is started by dividing the numeral into 12 zones. The numbers 1-12 are referenced for each zone. The possible values of Loop zone attribute in each zone are "true" and "false". The meaning of "true" is that the zone contains the loop of the numeral. The Endpoint attribute being "true" means that this zone contains the end point of the numeral. There are 24 attributes now. The Feature code attribute tells us how many lines of a numeral are passed by the referenced line. There are 7 referenced lines used in this experiment. The total attributes are 31. All attributes are used for construction of the classification rules by the Ant-miner algorithm in order to classify 10 numerals. The Ant-miner algorithm is adapted with a little change in this experiment for a better recognition rate. The results showed the system can recognize all of the training set (a thousand items of data from 50 people). When the unseen data is tested from 10 people, the recognition rate is 98 %.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.818-823
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• 2008

In this paper, we propose a feature extraction method which extracts directional features of handwritten numerals by using the projection runlength. Our directional featrures are obtained from four directional images, each of which contains horizontal, vertical, right-diagonal and left-diagonal lines in entire numeral shape respectively. A conventional method which extracts directional features by using Kirsch masks generates edge-shaped double line directional images for four directions, whereas our method uses the projections and their runlengths for four directions to produces single line directional images for four directions. To obtain the directional projections for four directions from a numeral image, some preprocessing steps such as thinning and dilation are required, but the shapes of resultant directional lines are more similar to the numeral lines of input numerals. Four [$4{\times}4$] directional features of a numeral are obtained from four directional line images through a zoning method. By using a hybrid feature which is made by combining our feature with the conventional features of a mesh features, a kirsch directional feature and a concavity feature, higher recognition rates of the handwrittern numerals can be obtained. For recognition test with given features, we use a multi-layer perceptron neural network classifier which is trained with the back propagation algorithm. Through the experiments with the handwritten numeral database of Concordia University, we have achieved a recognition rate of 97.85%.

• Journal for History of Mathematics
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• v.2 no.1
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• pp.9-27
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• 1985

Islam toot a great interest in the utility sciences such as mathematics and astronomy as it needed them for the religious reasons. It needeed geometry to determine the direction toward Mecca, its holiest place: arithmetic and algebra to settle the dates of the festivals and to calculate the accounts lot the inheritance; astronomy to settle the dates of Ramadan and other festivals. Islam expanded and developed mathematics and sciences which it needed at first for the religious reasons to the benefit of all mankind. This thesis focuses upon the golden age of Islamic culture between 7th to 13th century, the age in which Islam came to possess the spirit of discovery and learning that opened the Islamic Renaissance and provided, in turn, Europeans with the setting for the Renaissance in 14th century. While Europe was still in the midst of the dark age of the feudal society based upon the agricultural economy and its mathematics was barey alive with the efforts of a few scholars in churches, the. Arabs played the important role of bridge between civilizations of the ancient and modern times. In the history of mathematics, the Arabian mathematics formed the orthodox, not collateral, school uniting into one the Indo-Arab and the Greco-Arab mathematics. The Islam scholars made a great contribution toward the development of civilization with their advanced the development of civilization with their advanced knowledge of algebra, arithmetic and trigonometry. the Islam mathematicians demonstrated the value of numerals by using arithmetic in the every day life. They replaced the cumbersome Roman numerals with the convenient Arabic numerals. They used Algebraic methods to solve the geometric problems and vice versa. They proved the correlation between these two branches of mathematics and established the foundation of analytic geometry. This thesis examines the historical background against which Islam united and developed the Indian and Greek mathematics; the reason why the Arabic numerals replaced the Roman numerals in the whole world: and the influence of the Arabic mathematics upon the development of the modern mathematics.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.11-14
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• 1995

A Fuzzy Classifier which deals with very confusing objects is proposed. Naturally this classifier heavily relies on the nulti-feature decision-making procedure. For a simple example, this classifier is applied to the recognition of confusing handwritten numerals 4,6 and 9 The characteristic variables used in this paper are the existence of a loop and the relative location of the starting or ending points(SEP). Thus each sample of handwritten numerals 4, 6 and 9 is classified in one of the 6 groups which are divided according to the sample structure. Each group has its own classifying rules. Also the method of rule-generation using genetic algorithms in each group is proposed.

• Journal of Information Processing Systems
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• v.13 no.1
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• pp.174-183
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• 2017

In this paper, we propose a novel feature for recognizing handwritten Odia numerals. By using polygonal approximation, each numeral is segmented into segments of equal pixel counts where the centroid of the character is kept as the origin. Three primitive contour features namely, distance (l), angle (${\theta}$), and arc-tochord ratio (r), are extracted from these segments. These features are used in a neural classifier so that the numerals are recognized. Other existing features are also considered for being recognized in the neural classifier, in order to perform a comparative analysis. We carried out a simulation on a large data set and conducted a comparative analysis with other features with respect to recognition accuracy and time requirements. Furthermore, we also applied the feature to the numeral recognition of two other languages-Bangla and English. In general, we observed that our proposed contour features outperform other schemes.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.705-708
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• 1998

In this paper, a new algorithm is proposed that the template matching is used to devide SOFM (self-organizig feature map) for fast learning and to extract features for considering input data types. In order to verify the superoprity of the proposed algorithm, applied to the recognition of handwritten numerals. Templates of handwritten numerals are created by a line of external-contact.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.106-113
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• 2000

본 논문은 다량우편물의 대부분을 차지하는 창이 있는 봉투와 최근 증가되고 있는 명도 값이 높은 색깔이 있는 우편봉투 영상에서 구조적 방법을 분석하여 수취인 주소 영역을 자동적으로 추출하고 추출된 영역에서 우편번호를 찾아 제안된 신경망으로 인식 및 검증할 수 있는 실용적인 시스템을 구현하였다.