• Asian Pacific Journal of Cancer Prevention
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• 제17권7호
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• pp.3357-3362
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• 2016

Purpose: To correlate ultrasonographic (US) features of medullary thyroid carcinoma (MTC) with preoperative and post-operative calcitonin levels. Materials and Methods: A total of 130 thyroid nodules diagnosed as MTC were evaluated. Two radiologists retrospectively evaluated preoperative US features according to size, shape, margin, echogenicity, type of calcification, and lymph node status. Postoperative clinical and imaging follow-up (mean duration $31.9 {\pm} 22.5$ months) was performed for detection of tumor recurrence. US features, presence of LN metastasis, and tumor recurrence were compared between MTC nodules with and without elevated preoperative calcitonin (>100 pg/mL). Those with normalized and non-normalized postoperative calcitonin levels groups were also compared. Results: Common US features of MTCs were solid internal content (90.8%), irregular shape (44.6%), circumscribed margin (46.2%), and hypoechogenicity (56.2%). Comparing MTC nodules with and without elevated preoperative calcitonin levels, the size and shape of MTC nodule and lymph node metastasis showed statistical significance (p<0.05). Postoperative calcitonin normalization correlated with US features of tumor size (p=0.002), margin (p=0.034), shape ($p{\leq}0.001$), and presence of calcification (p=0.046). Tumor recurrence and LN metastasis were more prevalent in patients without normalization of postoperative calcitonin than in those with normalization (p=0.001). Conclusions: Serum calcitonin measurement is helpful for early diagnosis and predicting prognosis. Postoperative calcitonin measurement is also important for postoperative US follow up, especially in cases with larger nodule size, presence of calcification, irregular shape, and irregular margin.

• 한국인쇄학회지
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• 제6권1호
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• pp.41-57
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• 1988

Recently, it Is required to develop OCR(Optical Character Reader) along with the progress of the information processing system for Hangeul. Characters have to be recognized clearly so that OCR can be applied, Structure analysis method and lump method are used for the recognition of characters, and OCR is now available for the recognition of printed characters and handwritten alphanumeric characters having simple structure by them However, It is known that there should be much more study on the development of handwritten Hangout's OCR. This paper proposed a new method for the handwritten Hangout character recognition. The units of Initial consonant of Hangout are separated and then recognized from the utilization of the position- Information of Hangeul's units from the normalized patterns using the regression line theory. It is carried out for the extraction of the block which exists in the virtual Initial consonant region from the normalized input patterns and the calculation on maximum value (${\beta}$) of likelihood after comparing the features of separated subpattern with the initial consonant dictionary.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권7호
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• pp.2400-2419
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• 2014

Pre-segmented pixels can reduce the difficulty of segmentation and promote the segmentation performance. This paper proposes a novel segmentation method based on merging texture superpixels by computing inner similarity. Firstly, we design a set of Gabor filters to compute the amplitude responses of original image and compute the texture map by a salience model. Secondly, we employ the simple clustering to extract superpixles by affinity of color, coordinates and texture map. Then, we design a normalized histograms descriptor for superpixels integrated color and texture information of inner pixels. To obtain the final segmentation result, all adjacent superpixels are merged by the homogeneity comparison of normalized color-texture features until the stop criteria is satisfied. The experiments are conducted on natural scene images and synthesis texture images demonstrate that the proposed segmentation algorithm can achieve ideal segmentation on complex texture regions.

• 음성과학
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• 제15권4호
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• pp.85-96
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• 2008

Automatic speech recognition has severe performance degradation under noisy environments. To cope with the noise problem, many methods have been proposed. Most of them focused on noise-robust features or model adaptation. However, researchers have overlooked utterance verification (UV) under noisy environments. In this paper we discuss UV problems based on the normalized confidence measure. First, we show that UV performance is also degraded in noisy environments with the experiments of an isolated word recognition. Then we observe how the degradation of UV performances is suffered. Based on the UV experiments we propose a modeling method of the statistics of phone confidences using sigmoid functions. For obtaining the parameters of the sigmoidal models, the particle swarm optimization (PSO) is adopted. The proposed method improves 20% rejection performance. Our experimental results show that the PSO-NCM can apply noise speech recognition successfully.

• 대한전자공학회논문지
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• 제24권5호
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• pp.905-913
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• 1987

This paper presents a speaker dependent isolated digit recognition algorithm using the Mellin transform. Since the Mellin transform converts a scale information into a phase information, attempts have been made to utilize this scale invariance property of the Mellin transform in order to alleviate a time-normalization procedure required for a speech recognition. It has been found that good results can be obtained by taking the Mellin transform to the features such as a ZCR, log energy, normalized autocorrelation coefficients, first predictor coefficient and normalized prediction error. We employed a difference function for evaluating a similarity between two patterns. When the proposed algorithm was tested on Korean digit words, a recognition rate of 83.3% was obtained. The recognition accuracy is not compatible with the other technique such as LPC distance however, it is believed that the Mellin transform can effectively perform the time-normalization processing for the speech recognition.

• 한국정밀공학회지
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• 제15권11호
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• pp.189-198
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• 1998

Recently, monitoring of tool life is a matter of common interesting because tool life affects precision, productivity and cost in machining process. Especially flank wear has a direct effect on cutting mechanism, so the various pattern of cutting force is obtained experimentally according to variation of wear condition. By investigating cutting force signal, AR(Autoregressive) modeling and correlation dimension analysis is conducted in turning operation. In this modeling and analysis, we extract features through 6th AR model, correlation integral and normalized correlation integral. After the back-propagation model of the neural network is utilized to monitor tool life according to flank wear. As a result. a very reliable classification of tool life was obtained.

• Genomics & Informatics
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• 제18권4호
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• pp.41.1-41.8
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• 2020

We provide an algorithm for the construction and analysis of autocorrelation (information) functions of gene nucleotide sequences. As a measure of correlation between discrete random variables, we use normalized mutual information. The information functions are indicative of the degree of structuredness of gene sequences. We construct the information functions for selected gene sequences. We find a significant difference between information functions of genes of different types. We hypothesize that the features of information functions of gene nucleotide sequences are related to phenotypes of these genes.

• 한국정보통신학회논문지
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• 제18권12호
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• pp.2831-2838
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• 2014

논문에서는 정규화된 우세한 기울기 벡터들을 기반으로 직선 획들을 추출하고, 직선 획들의 교차영역의 형태와 세기에 의한 변형에 강건한 오프라인 필기 순서도 기호인식 알고리즘을 제안한다. 제안된 알고리즘에서는 먼저 곡선으로만 구성되는 연결기호들을 별도의 특징을 사용하여 인식하고, 직선 획들이 있는 다른 기호들은 정규화된 우세한 기울기 벡터 군집의 최소 외접사각형들을 구하여 직선 획들을 추출하고, 이들 사각형들의 교차영역 형태와 세기를 구하여 순서도 기호를 인식한다. 제안된 알고리즘의 타당성을 확인하기 위하여 컴퓨터 프로그램의 순서도에 주로 사용되는 10종류의 순서도 기호 198개를 취득하여 실험한 결과 99.5%의 인식률을 얻었고, 변형에 강건하게 순서도 기호들이 인식됨을 알 수 있어서 제안된 알고리즘이 오프라인 필기 순서도 기호인식에 매우 효과적임을 확인하였다.

• 한국측량학회지
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• 제36권6호
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• pp.433-442
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• 2018

저수구역은 계획된 홍수위에 의하여 둘러싸인 지역 혹은 댐의 계획된 홍수위 내에 있는 지역으로 정의된다. 본 연구에서는 저수구역 내 농경지를 탐지하기 위하여, 대표적인 기계학습 기법인 RF (Random Forest) 기반의 감독 분류 방법을 적용하였다. 저수구역 내의 농경지를 효과적으로 분류하기 위하여, 질감정보를 정량화하기 위한 대표적인 기법인 GLCM (Gray Level Co-occurrence Matrix)과 NDWI (Normalized Difference Water Index), NDVI (Normalized Difference Vegetation Index)를 추가적인 입력자료로 활용하였다. 특히, 질감정보를 생성하는데 사용된 윈도우 크기가 농경지의 분류 정확도에 미치는 영향을 분석하여, 저수구역 내의 농경지를 효과적으로 분류하기 위한 방법론을 제시하였다. 실험결과, UAV 영상을 이용한 분류결과를 통하여 취득된 다중분광영상과 NDVI, NDWI, GLCM 영상들을 이용하여 저수구역 내의 농경지를 효과적으로 탐지할 수 있음을 확인하였다. 또한, GLCM의 윈도우 크기가 분류정확도를 향상시키기 위한 중요한 변수임을 확인하였다.

• 전자공학회논문지B
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• 제29B권11호
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• pp.102-110
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• 1992

In this paper, a new method of character recognition is proposed. It uses density information, in addition to positional and directional information generally used, to recognize a character. Four directional feature primitives are extracted from the thinning templates on the observation that the output of the templates have directional property in general. A simple and fast feature extraction scheme is possible. Features are organized from recursive nonary tree(N-tree) that corresponds to normalized character area. Each node of the N-tree has four directional features that are sum of the features of it's nine sub-nodes. Every feature primitive from the templates are added to the corresponding leaf and then summed to the upper nodes successively. Recognition can be accomplished by using appropriate feature level of N-tree. Also, effectiveness of each node's feature vector was tested by experiment. A method to implement the proposed feature vector organization algorithm into hardware is proposed as well. The third generation node, which is 4$\times$4, is used as a unit processing element to extract features, and it was implemented in hardware. As a result, we could observe that it is possible to extract feature vector for real-time processing.