• Proceedings of the Korean Information Science Society Conference
• /
• 2005.07b
• /
• pp.757-759
• /
• 2005

Henry의 지문분류법이 창안된 후, 지문분류에 대한 여러 가지 접근 방법이 연구되고 있다. 특이점에 의한 분류는 가장 많이 연구되고 있는 방법이지만, 지문영상의 품질에 민감하기 때문에 정확한 분류가 쉽지 않다. 의사 융선은 특이점과 더불어 지문을 분류하기 위한 특징으로, 특이점의 불완전함을 보완하는데 이용한다. 본 논문에서는 나이브 베이즈 분류기를 이용하여 특이점과 의사 융선 정보의 확률적인 분류 방법을 제안한다. NIST DB 4에 대해 제안하는 방법을 실험한 결과 5클래스 분류에 대해 $85.4\%$의 분류율을 획득하였으며, 제안하는 방법이 신경망, 최근접 이웃에 의한 분류에 비해 더 빠르다는 것을 확인하였다.

• The Korean Journal of Applied Statistics
• /
• v.22 no.5
• /
• pp.911-921
• /
• 2009

Receiver Operating Characteristic(ROC) and Cumulative Accuracy Profile(CAP) curves are two methods used to assess the discriminatory power of different credit-rating approaches. The points of optimal classification accuracy on an ROC curve and of maximal profit on a CAP curve can be found by using iso-performance tangent lines, which are based on the standard notion of accuracy. In this paper, we offer an alternative accuracy measure called the true rate. Using this rate, one can obtain alternative optimal threshold points on both ROC and CAP curves. For most real populations of borrowers, the number of the defaults is much less than that of the non-defaults, and in such cases the true rate may be more efficient than the accuracy rate in terms of cost functions. Moreover, it is shown that both alternative scores of optimal classification accuracy and maximal profit are the identical, and this single score coincides with the score corresponding to Kolmogorov-Smirnov statistic used to test the homogeneous distribution functions of the defaults and non-defaults.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2004.05b
• /
• pp.468-471
• /
• 2004

In this paper, a method for classifying fingerprint ridge lines using runlength codes is proposed. To detect feature points(minutiae) in automatic fingerprint identification system(AFIS), classification of fingerprint ridge lines are essential process. The fingerprint ridge lines are classified by run-length coding, and also the end and bifurcation regions in ridge lines are separated. To evaluate the performance of the proposed method, detected feature regions including minutiae points and classified fingerprint ridge lines are shown.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2000.11a
• /
• pp.319-322
• /
• 2000

본 논문에서는 지문영상으로부터 제안한 알고리즘을 이용하여 특이점(Core, Delta)을 추출한 후 특이점의 개수와 종류에 따라서 5가지 부류(arch, tented arch, left loop, right loop, whorl)로 지문영상을 분류하였다. 지문영상을 8*8블록과 16*16블록으로 분할한 후 3*3 Sobel 마스크를 씌워서 대표 방향을 구하였다. 또한 블록으로 분할한 영상으로부터 분산을 구하여 전경과 배경을 분리(segmentation)시켜 수행속도를 향상시켰다. 전처리 과정으로는 일정한 블록마다 임계값을 다르게 적용시키는 블록 이진화 기법을 사용하였으며 특이점을 추출하기 위해서 서로 크기가 다른 2개의 블록으로 영상을 분할하였다. 우선 8*8블록으로 영역을 분할한 후 방향 성분을 구하고 특이점들을 추출하였다. 이 경우 잡영 때문에 특이점이 너무 많이 추출되는 문제점이 있으므로 이러한 해결책으로 16*16블록으로 영역을 분할하여 방향 성분을 구하고 특이점을 추출하였다. 이렇게 다른 두 영역에서 동시에 나타나는 특이점을 후보 특이점으로 잡아서 그 후보 특이점 주변으로 Poincare 지수를 적용하여 확실한 특이점을 선택한 후 5가지의 지문 형태로 분류하였다. 실험결과 대부분의 지문영상에 대하여 강건한 분류 특성을 보이고 있음을 확인하였다.

• The Korean Journal of Applied Statistics
• /
• v.27 no.5
• /
• pp.773-786
• /
• 2014

We propose the multiplication of false rates (MFR) which is a classification accuracy criteria and an area type of rectangle from ROC curve. Optimal threshold obtained using MFR is compared with other criteria in terms of classification performance. Their optimal thresholds for various distribution functions are also found; consequently, some properties and advantages of MFR are discussed by comparing FNR and FPR corresponding to optimal thresholds. Based on general cost function, cost ratios of optimal thresholds are computed using various classification criteria. The cost ratios for cost curves are observed so that the advantages of MFR are explored. Furthermore, the de nition of MFR is extended to multi-dimensional ROC analysis and the relations of classification criteria are also discussed.

• The Korean Journal of Applied Statistics
• /
• v.34 no.5
• /
• pp.807-822
• /
• 2021

Various accuracy measures that can be explained on the odds curve are discussed, and an alternative accuracy measure, the maximum square, is proposed based on the characteristics of the odds curve. Thresholds corresponding to these accuracy measures are obtained by considering various probability distribution functions and an illustrative example. Their characteristics are discussed while comparing many kinds of statistics measuring thresholds. Therefore, we can conclude that optimal thresholds could be explored from the odds curve, similar to the ROC curve, and that the maximum square measure can be used as a good accuracy measure that can improve the performance of the binary classification model.

• The Korean Journal of Applied Statistics
• /
• v.23 no.1
• /
• pp.13-28
• /
• 2010

Assuming a mixture distribution for credit evaluation studies, we discuss estimating threshold methods to minimize errors that default borrowers are predicted as non defaults or non defaults are regarded as defaults. A method by using statistical hypotheses tests, the most powerful test and generalized likelihood ratio test, for the probability density functions which are defined with the score random variable and the parameter space consisted of only two elements such as the default and non default states is proposed to estimate a threshold. And anther optimal thresholds to maximize classification accuracy measures of the accuracy and the true rate for ROC and CAP curves are estimated as equations related with these probability density functions. Three kinds of optimal thresholds in terms of the hypotheses testing, the accuracy and the true rate are obtained from normal random samples with various means and variances. The sums of the type I and type II errors corresponding to each optimal threshold are obtained and compared. Finally we discuss about their efficiency and derive conclusions.

• The Korean Journal of Applied Statistics
• /
• v.32 no.2
• /
• pp.187-198
• /
• 2019

Extensive literature exists on how to estimate optimal thresholds based on various accuracy measures using receiver operating characteristic (ROC) and cumulative accuracy profile (CAP) curves. This paper now proposes an alternative measure to represented the specific partial area under the ROC and CAP curves. The relationship between ROC and CAP functions is examined using differential equations of the new defined partial area under curves. In addition, the relationship with the optimal thresholds under conditions of various accuracy measures for the ROC and CAP functions is also derived. We assume there are two kinds of distribution functions composing the mixed distribution as various normal distributions before finding the optimal thresholds. Corresponding type 1 and 2 errors are also explored and discussed under various conditions for accuracy measures.

• The Korean Journal of Applied Statistics
• /
• v.35 no.1
• /
• pp.77-91
• /
• 2022

The optimal threshold estimation is considered in order to discriminate the mixture distribution in the fields of Biostatistics and credit evaluation. There exists well-known various accuracy measures that examine the discriminant power. Recently, Matthews correlation coefficient and the F1 statistic were studied to estimate optimal thresholds. In this study, we explore whether these accuracy measures are appropriate for the optimal threshold to discriminate the mixture distribution. It is found that some accuracy measures that depend on the sample size are not appropriate when two sample sizes are much different. Moreover, an alternative method for finding the optimal threshold is proposed using the correlation coefficient that defines the ratio of the confusion matrix, and the usefulness and utility of this method are also discusses.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.13 no.5
• /
• pp.545-551
• /
• 2003

Henry System which is a traditional fingerprint classification model is difficult to apply to a modem Automatic Fingerprint Identification System (AFIS). To tackle this problem, this study is to apply algorithm for an An Ensemble Fingerprint Classroom System using changes of gradient of ridge in order to improve precise joining speed of a large volume of database. The existing classification system, Henry System, is useful in a captured fingerprint image of core point and delta point using paper and ink. However, the Henry System is unapplicable in modem Automatic Fingerprint Identification System (AFIS) because of problems such as size of input sensor and way of input. This study is to suggest an Ensemble Fingerprint Classroom System which can classify 5 basic patterns of Henry System in uncaptured delta image using changes of gradient of ridge. The proposed fingerprint classification technique will make an improvement of precise joining speed by reducing data volume.