• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.7C
• /
• pp.712-718
• /
• 2003

C.elegans are often used to study of function of gene, but it is difficult for human observation to distinguish the mutants of C.elegans. To solve this problem, the system, which can classify the mutant types automatically using the computer vision, is now studying. Tn previous work［1］, we described the preprocessing method for automated-classification system. In this paper, we introduce shape features, which can be extracted from an acquisition image. We divide the feature into two categories, which are related to size and posture of the worm, and each feature is described mathematically We validate the shape information experimentally. And we use hierarchical clustering algorithm for classification. It reveals that 4 mutants of the worm, which are used in experiment, can be classified with over 90% of success rate.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.10
• /
• pp.2223-2230
• /
• 2011

ECG is used to diagnose heart diseases such as myocardial ischemia, arrhythmia and myocardial infarction. Particularly, myocardial ischemia causes the shape change of the ST segment, this change is transient and may occur without symptoms. So it is important to detect the transient change of ST segment through long term monitoring. ST segment classification algorithm for making diagnosis myocardial ischemia is presented in this paper. The first step in the ST segment shape classification process is to detect R wave point and feature points based adaptive threshold and window. And then, the suggested algorithm detects the ST level change, To classify the ST segment shape, the suggested algorithm uses the slope values of the four points between the S and T wave. The ECG data in the European ST-T database were used to verify the performance of the developed algorithm. The best correct rate was 99.40% and the worst correct rate was 68.48%.

• The Research Journal of the Costume Culture
• /
• v.13 no.2 s.55
• /
• pp.200-208
• /
• 2005

This study was aimed to provide the measurement data and shape classification of the head of the Korean female children for the headwear sizing systems. Four hundred nineteen female children, aged nine to twelve years, participated for this study. The 19 regions on the head and height, weight of the subjects were directly measured by the expert experimenters. Factor analysis, cluster analysis, GLM analysis and Tukey HSD test were performed using these data. Through factor analysis, five factors were extracted upon factor scores and those factors comprised $71.318\%$ for the total variances. Three clusters as their head shape were categorized using fiver factor scores by cluster analysis. Type 1 was characterized by the widest head width, Bitragion arc, and shortest head length, and medium height and weight. Type 2 had the longest head length and the widest side head width and the highest head circumference, and highest height and largest weight. Type 3 was characterized by the medium head length, smallest head circumstance, narrowest head width and side head width, and smallest height and weight.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2001.01a
• /
• pp.421-427
• /
• 2001

In this paper, a method for selection of the optimal feature vectors is proposed for the classification of closed 2D shapes using the bispectrum of a contour sequence. The bispectrum based on third order cumulants is applied to the contour sequences of the images to extract feature vectors for each planar image. These bispectral feature vectors, which are invariant to shape translation, rotation and scale transformation, can be used to represent two-dimensional planar images, but there is no certain criterion on the selection of the feature vectors for optimal classification of closed 2D images. In this paper, a new method for selecting the optimal bispectral feature vectors based on the variances of the feature vectors. The experimental results are presented using eight different shapes of aircraft images, the feature vectors of the bispectrum from five to fifteen and an weighted mean fuzzy classifier.

• Korean Journal of Remote Sensing
• /
• v.25 no.2
• /
• pp.145-154
• /
• 2009

High spatial resolution satellite image classification has a limitation when only using the spectral information due to the complex spatial arrangement of features and spectral heterogeneity within each class. Therefore, the extraction of the spatial information is one of the most important steps in high resolution satellite image classification. This study proposes a new spatial feature extraction method, named SSI(Shape-Size Index). SSI uses a simple region-growing based image segmentation and allocates spatial property value in each segment. The extracted feature is integrated with spectral bands to improve overall classification accuracy. The classification is achieved by applying a SVM(Support Vector Machines) classifier. In order to evaluate the proposed feature extraction method, KOMPSAT-2 and QuickBird-2 data are used for experiments. It is demonstrated that proposed SSI algorithm leads to a notable increase in classification accuracy.

• Journal of Internet Computing and Services
• /
• v.12 no.6
• /
• pp.117-128
• /
• 2011

In this paper, we present a novel approach for contents-based medication image retrieval from a medication image database using the shape classification and color information of the medication. One major problem in developing a contents-based drug image retrieval system is there are too many similar images in shape and color and it makes difficult to identify any specific medication by a single feature of the drug image. To resolve such difficulty in identifying images, we propose a hybrid approach to retrieve a medication image based on shape and color features of the medication. In the first phase of the proposed method we classify the medications by shape of the images. In the second phase, we identify them by color matching between a query image and preclassified images in the first phase. For the shape classification, the shape signature, which is unique shape descriptor of the medication, is extracted from the boundary of the medication. Once images are classified by the shape signature, Hue and Saturation(HS) color model is used to retrieve a most similarly matched medication image from the classified database images with the query image. The proposed system is designed and developed especially for specific population- seniors to browse medication images by using visual information of the medication in a feasible fashion. The experiment shows the proposed automatic image retrieval system is reliable and convenient to identify the medication images.

• Proceedings of the IEEK Conference
• /
• 2002.06a
• /
• pp.113-116
• /
• 2002

It is required to network to make more intelligent packet processing and forwarding for increasing bandwidth and various services. Classification provides these intelligent to network which is acquired by increasing number of rules in classification rule set. In this Paper, we propose a classification algorithm efficient to scalable rule set ahead as well as Present small rule set. This algorithm has competition to existing methods by performance and advantage that it is mixed with another algorithm because il does not change original shape of rule set.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.26 no.10
• /
• pp.1443-1454
• /
• 2002

The purposes of this study were to classify body type of adult males into several kind of shape and to provide the characteristics of size of each group which has same shape. As the sample, subjects were 1290 males of 20 to 54 year-old. The procedure and results were follows; 1. As the result of the previous reserch, the front line of body was classified in X, H, Y and A types. 2. The principal component analysis was used to obtain the shape factor of the side line of the trunk. 9 factors in the side were extracted. As the result of the cluster analysis of factor scores, the side line of body was classified in 5 types. It was named X, A, Y and H type in the front and S, D1, d, I and D2 type in the side. 3. In order to consider the shape of body as a whole, the body shape of the front and side were compounded. The whole body shapes of adult male were very various, and 6 body shapes, XS, YS, Yd, YI, AD2 and HD1 were selected as the basic types. In each type of body, several groups were classified by size factor, height and chest girth and master size was selected considering appearance frequency.

• Journal of the Korea Safety Management & Science
• /
• v.13 no.1
• /
• pp.195-202
• /
• 2011

The study interprets each of three classification models based on Bath-Tub Failure Rate (BTFR), Extreme Value Distribution (EVD) and Conjugate Bayesian Distribution (CBD). The classification model based on BTFR is analyzed by three failure patterns of decreasing, constant, or increasing which utilize systematic management strategies for reliability of time. Distribution model based on BTFR is identified using individual factors for each of three corresponding cases. First, in case of using shape parameter, the distribution based on BTFR is analyzed with a factor of component or part number. In case of using scale parameter, the distribution model based on BTFR is analyzed with a factor of time precision. Meanwhile, in case of using location parameter, the distribution model based on BTFR is analyzed with a factor of guarantee time. The classification model based on EVD is assorted into long-tailed distribution, medium-tailed distribution, and short-tailed distribution by the length of right-tail in distribution, and depended on asymptotic reliability property which signifies skewness and kurtosis of distribution curve. Furthermore, the classification model based on CBD is relied upon conjugate distribution relations between prior function, likelihood function and posterior function for dimension reduction and easy tractability under the occasion of Bayesian posterior updating.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.29 no.5 s.142
• /
• pp.737-744
• /
• 2005

This study was aimed to provide the measurement data and shape classification of the head of the Korean male children for the headwear sizing systems. Five hundred twenty male children, aged nine to twelve years, participated f3r this study. The 17 regions on the head and height, weight of the subjects were directly measured by the expert experimenters. Factor analysis, cluster analysis, GLM analysis and Tukey HSD test were performed using these data. Through factor analysis, low factors were extracted upon factor scores and those factors comprised $69.76\%$ for the total variances. Three clusters as their head shape were categorized using four factor scores by cluster analysis. Type 1 was characterized by the widest width and Bitragion arc, shortest head length. Type 2 had the longest head length and the widest side width and the highest head length and head circumference. Type 3 was characterized by the smallest head circumstance, head width and side width, and medium head length.