• Korean Journal of Computational Design and Engineering
• /
• v.11 no.1
• /
• pp.1-10
• /
• 2006

This paper addresses B-spline curve approximation of a set of ordered points to a specified toterance. The important issue in this problem is to reduce the number of control points while keeping the desired accuracy in the resulting B-spline curve. In this paper we propose a new method for error-bounded B-spline curve approximation based on adaptive selection of dominant points. The method first selects from the given points initial dominant points that govern the overall shape of the point set. It then computes a knot vector using the dominant points and performs B-spline curve fitting to all the given points. If the fitted B-spline curve cannot approximate the points within the tolerance, the method selects more points as dominant points and repeats the curve fitting process. The knots are determined in each step by averaging the parameters of the dominant points. The resulting curve is a piecewise B-spline curve of order (degree+1) p with $C^{(p-2)}$ continuity at each knot. The shape index of a point set is introduced to facilitate the dominant point selection during the iterative curve fitting process. Compared with previous methods for error-bounded B-spline curve approximation, the proposed method requires much less control points to approximate the given point set with the desired shape fidelity. Some experimental results demonstrate its usefulness and quality.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.9
• /
• pp.2412-2420
• /
• 1997

An algorithm for detecting dominant points on a digital contour is proposed. The algorithm detects the dominant points from the given contour with the given number of points as a constraint condition. on the basis of the principle of the top-down approach. The dominant points are detected by minimizing the object function that presents the similarity between the given contour and the approximated polygon drawn by connecting the dominant points of candicate. The penalty multiplier method is applied to minimize the augmented Lagrangean function which is made by adding the penalty of the constraint condition to the object function. On the minimization, a local searching method by the partial problem division is considered, and it is clarified that the reasonable solution is obtained by the method. The proposed algorithm has a merit that the dominant points can be detected exactly and stably even for the digital contour composed of multiple-scale features and the similar contours, because it detects them on considering the property of a whole figure of the given contour. It is confirmed that the proposed algorithm is more excellent than other previously proposed algorithms by the comparison and the evaluation through the experiment on suing typical digital curves.

• Journal of Korean Institute of Industrial Engineers
• /
• v.25 no.4
• /
• pp.437-447
• /
• 1999

Previous researches on risk attitudes or on the typical utility functions have mostly focused on how the risk attitude of decision maker varies when changes are made in one or two lottery reference points such as consequence domain and magnitude of probability under assumed risk situations represented by simple lotteries. It is, however, very difficult to forecast dominant risk attitudes under risk situations which exhibit a complex combination of many reference points. In this study, twelve risk situations which a decision maker may confront in real decision-making situations were formulated by combining in various ways three reference points, that is, magnitude of probability, consequence domain, and magnitude of gain or loss. Then through a questionnaire dominant risk attitudes under every assumed risk situation were investigated, and the general shape of utility function implied by the experimental results were derived. Results of the present study show that none of the three reference points have dominant effect over the others due to complicated interaction between them, and given the twelve risk situations the observed risk attitude widely varies from strong risk taking to strong risk aversion.

• ETRI Journal
• /
• v.32 no.4
• /
• pp.630-633
• /
• 2010

In this letter, we propose a novel polygonal approximation of digital curves that preserve original shapes. The proposed method first detects break points, which have two different consecutive vectors, and sets an initial dominant point set. The approximation is then performed iteratively by deleting a dominant point using a novel distance, which can measure both the distance and the angle acuteness. The experimental results show that the proposed method can preserve original shapes and is appropriate for various shapes, including slab-sided shapes.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.3
• /
• pp.79-87
• /
• 1996

A new method for recognizing and locating partially occluded or overlapped two-dimensional objects regardless of their size, translation, and rotation, is presented. Dominant points approximating occuluding contoures of objects are generated by finding local maxima of smoothed k-cosine function, and then used to guide the contour segment matching procedure. Primitives between the dominant points are produced by projecting the local contours onto the line between the dominant points. Robust classification of primitives. Which is crucial for reliable partial shape matching, is performed using adaptive resonance theory (ART2). The matched primitives having similar scale factors and rotation angles are detected in the hough space to identify the presence of the given model in the object scene. Finally the translation vector is estimated by minimizing the mean squred error of the matched contur segment pairs. This model-based matching algorithm may be used in diveerse factory automation applications since models can be added or changed simply by training ART2 adaptively without modifying the matching algorithm.

• The KIPS Transactions:PartB
• /
• v.18B no.6
• /
• pp.375-384
• /
• 2011

This paper suggests a method to recognize facial expressions of animation characters by means of dominant colors and feature points. The proposed method defines a simplified mesh model adequate for the animation character and detects its face and facial components by using dominant colors. It also extracts edge-based feature points for each facial component. It then classifies the feature points into corresponding AUs(action units) through neural network, and finally recognizes character facial expressions with the suggested AU specification. Experimental results show that the suggested method can recognize facial expressions of animation characters reliably.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.22 no.7
• /
• pp.1523-1533
• /
• 1997

Image registration is concerned with the establishment of correspondence between images of the same scene with translational, rotational, and scaling differences. The estimated transformation parameters between images are very important information in the field of many applications. In this paper, we propose a shape matching scheme for finding correspondence points for images with various differences, Tranditional solutions to this area are unreliable for the rotational and schaling changes between images, and the feature extraction of partially occluded scene. To solve those problems, dominant points on digital curves are detected by scale-space filtering, and initial matching is performed by similarity measure of cumulative curvatures for dominant points. For initial matching segments pairs, optimal matching points are calculated using dynamic programming.Finally, transformation parameters are estimated.

• The Journal of Internal Korean Medicine
• /
• v.42 no.4
• /
• pp.707-717
• /
• 2021

Objectives: The aim of this study was to introduce the normalization effects of stimulation of both ST36 and CV11, 12, 13 meridian points on the abnormal gastric myoelectrical activity in two cases of functional dyspeptic patients with gastric dysmotility. Methods: Gastric myoelectrical activity was recorded by electrogastrography every two weeks until their gastric myoelectrical activity finally reached the normality. Dominant frequency of gastric slow waves in the fasting and postprandial periods and a dominant power ratio were obtained on each occasion. Patients were treated three times each day: 9 am, 1 pm, and 7 pm. The first treatment consisted of manual and immersion stimulation on all used meridian points for 20 min. In the second and third treatments, electrical stimulation of both ST36 was added. It was conducted for 20 min at a strength intensity of 1.2 times the pain threshold at a frequency of 3 Hz. Results: Stimulation of the above meridian points normalized abnormal gastric myoelectrical activity. The time taken to return from abnormal gastric myoelectrical activity to normal was 16-19 weeks. Conclusion: Stimulation of both ST36 and CV11, 12, 13 meridian points normalized the abnormal gastric myoelectrical activity in the functional dyspepsia of gastric dysmotility.

• Journal of the Institute of Electronics Engineers of Korea TE
• /
• v.39 no.1
• /
• pp.37-45
• /
• 2002

This paper proposes new features for recognizing telltale bulb in a cluster. A typical feature employed in model-based pattern recognition is polygonal approximation points of object. But recognition using these dominant points has many mismatching counts in small model such as telltale bulb. To reduce mismatching counts, proposed features are the circle distribution of object pixel and the ratio of distance from center to boundary in object. This Paper also proposes new decision function using three features. In simulation result, we make a comparison mismatching counts between recognition using dominant points and the new recognition algorithm using three features.

• International Journal of Aeronautical and Space Sciences
• /
• v.17 no.4
• /
• pp.622-630
• /
• 2016

In the operation of a low earth orbit satellite, a series of antenna commands are transmitted from a ground station to the satellite within a visibility window (i.e., the time period for which an antenna of the satellite is visible from the station) and executed to control the antenna. The window is a limited resource where all data transmission is carried out. Therefore, minimizing the transmission time for the antenna commands by reducing the data size is necessary in order to provide more time for the transmission of other data. In this paper, we propose a geometric compression method based on B-spline curve fitting using dominant points in order to compactly represent the antenna commands. We transform the problem of command size reduction into a geometric problem that is relatively easier to deal with. The command data are interpreted as points in a 2D space. The geometric properties of the data distribution are considered to determine the optimal parameters for a curve approximating the data with sufficient accuracy. Experimental results demonstrate that the proposed method is superior to conventional methods currently used in practice.