• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.9
• /
• pp.1070-1075
• /
• 2019

In this paper, I propose an algorithm to generate an input digit image for a digit recognition system by detecting a digit string in an image and segmenting the digits constituting the digit string. The proposed algorithm detects blobbed digit string through blob detection, designates a digit string area and corrects digit string skew using the detected blob information. And the proposed algorithm corrects the digit skew and determines the boundary points for the digit segmentation in the corrected digit sequence using three CPgraphs newly defined in this paper. In digit segmentation experiments using the image group including digit strings printed with a range of the font sizes and the image group including handwritten digit strings, the proposed algorithm successfully segments 100% and 90% of the digits in each image group.

• Journal of Korea Society of Industrial Information Systems
• /
• v.6 no.1
• /
• pp.82-89
• /
• 2001

This paper presents recognition of unconstrained handwritten numeral strings using decision value generator, which is combined with both isolated digit identifier and recognizer designed with structural characteristics of digits. Numerical string recognition system is composed of three modules, which are pre-segmentation, segmentation and recognition. Pre-segmentation module classifies a numeral string into sub-images, which are isolated digit, touched digits or broken digit, using confidence value of decision value generator. Segmentation module segments touched digits using reliability value of decision value generator that will separate the leftmost digit from touched string of digits. Segmentation-based and segmentation-free methods have used for classification and segmentation, respectively. To evaluate proposed method, experiments have carried out with handwritten numeral strings of NIST SD19 and higher recognition performance than previous works has obtained with 96.7%.

• Proceedings of the KIEE Conference
• /
• 1987.11a
• /
• pp.338-340
• /
• 1987

The speech recognition system usually consists of two modules, segmentation module and identification module. So, the performance of the system heavily depends on the segmentation accuracy and the segmentation unit. This paper is concerned with the agreeable features for segmentation in syllables. Total energy and two band width energy. (LE:4000-5000Hz and HE:900-3100Hz) are suitable cues for segmentation. And we testify it through the experiment using connected digit.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.17 no.3
• /
• pp.12-19
• /
• 1980

A speech recognition system for separately pronounced Korean digits is described. The system is composed of four stages ; parameter extraction, segmentation by voiced-unovied analysis, formant tracking and pattern matching. Digit speech is segmented into an unvoiced segment and/or a voiced one using ZCR and energy measurements, then to estimate the first three formant frequencies a relatively simple formant tracking scheme is applied to the raw formant data extracted from linear prediction spectra. Finally, pattern matching is made using dynamic programmig method. Recognition experiment is carried out for 150 digit utterences spoken by three male speakers, and recgnition rate 94 % is obtained.

• Proceedings of the Korean Information Science Society Conference
• /
• 2002.10d
• /
• pp.481-483
• /
• 2002

본 논문은 숫자간 접촉이 포함된 무제약 오프라인 필기 숫자열 인식을 위한 분할 및 인식기법을 소개하고자 한다. 시스템은 숫자열에서 접촉된 성분을 추출하는 모듈, 접촉된 숫자를 분할하는 모듈과 최종적으로 분할된 결과를 조합하는 모듈로 이루어진다. 그리고, 위의 기법을 NIST 데이터에 적용하여 제안한 분할 및 인식기법의 효율성을 보여준다.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.9
• /
• pp.19-25
• /
• 2016

This paper is to recognize and play tab chords from guitar musical sheets. The musical chord area of an input image is segmented by changing the image in saturation and applying the Grabcut algorithm. Based on a template matching, our approach detects tab starting sections on a segmented musical area. The virtual block method is introduced to search blanks over chord lines and extract tab fret segments, which doesn't cause the computation loss to remove tab lines. In the experimental tests, the prototype based classification outperforms Bayesian method and the nearest neighbor rule with the whole set of training data and its performance is similar to that of the support vector machine. The experimental result shows that the prediction rate is about 99.0% and the number of selected prototypes is below 3.0%.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2001.10a
• /
• pp.503-506
• /
• 2001

본 논문에서는 획의 일부분이 손상된 숫자(broken digit)나 붙은 숫자(touching digits)와 같은 비정형 숫자들이 포함된 필기체 숫자 열을 인식할 수 있는 방법에 대하여 제안하였다. 비정형 숫자들은 분류(pre-segmentation) 단계에서 숫자들의 구조적인 특징 정보를 이용하여 정형인 개별 숫자(isolated digit)로부터 획의 일부분이 손상된 숫자 또는 붙은 숫자들로 분류된다. 획의 일부분이 분리된 숫자의 결합 및 붙은 숫자들의 분할 단계를 거쳐 인식을 시도하였다. 제안된 방법의 타당성을 증명하기 위하여 NIST SDl9 데이터베이스를 이용하여 시뮬레이션 해 보았다.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.365-365
• /
• 2000

In this paper, we describe the system to recognize the six digit postal number of mails using neural network. Our zip-code recognition system consists of a preprocessing procedure for the original captured image, a segmentation procedure for separating an address block area with a shape, and recognition procedure for the cognition of a postal number. we extract the feature vectors that are the input of a neural network for the recognition process based on an area optimizing and an image thinning processing. The neural network classifies the zip-code in the mail and the recognized zip-code is verified through the zip-code database.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.10
• /
• pp.112-122
• /
• 1994

Number plates of vehicles operating in real world are sometimes difficult to recognize due to the number plate degradation (bent or dirty plates). To recognize the vehicle number from a number plate with severe degradation, good segmentation is necessary, which in turn requires good thresholding. This paper proposes a binarization method that combines the fast processing speed of global thresholding methods with the local thresholding methods' ability to adapt to lacal gray level characteristics. The proposed method overcomes the degradation of number plates quickly and maintains the widths of digit strokes uniform. The paper presents results of comparison with existing global and local thresholding methods.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.18 no.10
• /
• pp.1422-1432
• /
• 1993

Nonlinear mapping function of the HCNN( Hidden Control Neural Network ) can change over time to model the temporal variability of a speech signal by combining the nonlinear prediction of conventional neural networks with the segmentation capability of HMM. We have two things in this paper. first, we showed that the performance of the HCNN is better than that of HMM. Second, the HCNN with its prediction error measure given by weighted distance is proposed to use suitable distance measure for the HCNN, and then we showed that the superiority of the proposed system for speaker-independent speech recognition tasks. Weighted distance considers the differences between the variances of each component of the feature vector extraced from the speech data. Speaker-independent Korean digit recognition experiment showed that the recognition rate of 95%was obtained for the HCNN with Euclidean distance. This result is 1.28% higher than HMM, and shows that the HCNN which models the dynamical system is superior to HMM which is based on the statistical restrictions. And we obtained 97.35% for the HCNN with weighted distance, which is 2.35% better than the HCNN with Euclidean distance. The reason why the HCNN with weighted distance shows better performance is as follows : it reduces the variations of the recognition error rate over different speakers by increasing the recognition rate for the speakers who have many misclassified utterances. So we can conclude that the HCNN with weighted distance is more suit-able for speaker-independent speech recognition tasks.