• ETRI Journal
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• v.33 no.2
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• pp.259-266
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• 2011

We present a new method for an automated markerless system to describe, analyze, and classify human gait motion. The automated system consists of three stages: I) detection and extraction of the moving human body and its contour from image sequences, ii) extraction of gait figures by the joint angles and body points, and iii) analysis of motion parameters and feature extraction for classifying human gait. A sequential set of 2D stick figures is used to represent the human gait motion, and the features based on motion parameters are determined from the sequence of extracted gait figures. Then, a k-nearest neighbor classifier is used to classify the gait patterns. In experiments, this provides an alternative estimate of biomechanical parameters on a large population of subjects, suggesting that the estimate of variance by marker-based techniques appeared generous. This is a very effective and well-defined representation method for analyzing the gait motion. As such, the markerless approach confirms uniqueness of the gait as earlier studies and encourages further development along these lines.

• Journal of Korean Neurosurgical Society
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• v.53 no.6
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• pp.374-376
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• 2013

The abducens nerve paresis generally can aid in the presumptive diagnosis of abducens schwannoma along with the typical radiological features of schwannomas. The authors present a case of a 76-year-old male patient with a abducens schwannoma without abducens nerve paresis. Peroperatively, abducens nerve located in the cerebellopontine cistern had normal in contour and diameter, despite the mass originated from this nerve. We hypothesize that anatomic location of abducens nerve may affect the vector of tumor growth to prevent destruction of its origin, the abducens nerve.

• Korean Journal of Remote Sensing
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• v.23 no.3
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• pp.199-209
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• 2007

Traditionally, aerial images have been used as main sources for compiling topographic maps. In recent years, lidar data has been exploited as another type of mapping data. Regarding their performances, aerial imagery has the ability to delineate object boundaries but omits much of these boundaries during feature extraction. Lidar provides direct information about heights of object surfaces but have limitations with respect to boundary localization. Considering the characteristics of the sensors, this paper proposes an approach to extracting buildings from lidar and aerial imagery, which is based on the complementary characteristics of optical and range sensors. For detecting building regions, relationships among elevation contours are represented into directional graphs and searched for the contours corresponding to external boundaries of buildings. For generating building models, a wing model is proposed to assemble roof surface patches into a complete building model. Then, building models are projected and checked with features in aerial images. Experimental results show that the proposed approach provides an efficient and accurate way to extract building models.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1138-1156
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• 2021

Emotional semantics are the highest level of semantics that can be extracted from an image. Constructing a system that can automatically recognize the emotional semantics from images will be significant for marketing, smart healthcare, and deep human-computer interaction. To understand the direction of image emotion recognition as well as the general research methods, we summarize the current development trends and shed light on potential future research. The primary contributions of this paper are as follows. We investigate the color, texture, shape and contour features used for emotional semantics extraction. We establish two models that map images into emotional space and introduce in detail the various processes in the image emotional semantic recognition framework. We also discuss important datasets and useful applications in the field such as garment image and image retrieval. We conclude with a brief discussion about future research trends.

• Korean Journal of Cognitive Science
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• v.7 no.1
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• pp.37-56
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• 1996

In this paper,we design a verifier for unconstrained handwritten numerals using structural feature analysis,and use it as a comnination algorithm for multiple recognizers.The existing combination algorithms mainly use learnings,statistical methods,or probabilistic methods without considering structural features of numerals.That is why they cannot recognize some numerals which human can identify clearly.To overcome the shortcomings,we design one-to-one verifiers which compare and analyze the relative structural features between frequently confused numeral pairs,and apply them to combine multiple recongnizers.Structural features for verification consist of contour,direction al chain code,polygonal approximation,and zero crossing number of horizontal/vertical projections. We gained a 97.95% reliability with CENPARMI numeral data,and showed that some misconceived factors generated from typical combination algorithms can be removed.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.47 no.5
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• pp.360-364
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• 2021

Objectives: The purpose of this study was to evaluate the clinical and radiographic characteristics of idiopathic bone cavity (IBC) to determine the effect of surgical intervention on the process of healing. Materials and Methods: All cases diagnosed with IBC during the period of 2011 to 2020 at our Department of Oral and Maxillofacial Surgery were searched. Ninety cases were retrieved. The features evaluated were sex, age, contour of the lesion, number of teeth involved, site, history of trauma, and postoperative healing pattern. The significance of differences was assessed by Mann-Whitney U test and chi-square test. Results: The female:male ratio showed no predilection toward either sex (0.9:0.8). The mean age of the collected sample was 22.05±14.38 years, and the age ranged from 10 to 58 years. All cases presented in the mandible and showed well-circumscribed radiolucency. Margins were either scalloped or round in shape, and the size varied from one tooth to six teeth involvement. Seventy cases involved three or fewer roots. Three cases showed bilateral lesion. Four cases had a history of trauma at the area of the lesion. Fifty-one cases were followed for six months after surgery, and all showed increased bone density at the lesion. Conclusion: There is no definitive radiological or clinical feature of IBC. Considering the diversity of clinical and radiological features, such a diagnosis relies primarily on surgical findings of an empty bone cavity with no epithelial lining. Our data suggest that surgical intervention be the first choice of treatment as opposed to observation.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.119-128
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• 2002

This paper proposes an efficient recognition method of car license plate from the car images by using both the dynamical thresholding and the neural network with enhanced learning algorithm. The car license plate is extracted by the dynamical thresholding based on the structural features and the density rates. Each characters and numbers from the p]ate is also extracted by the contour tracking algorithm. The enhanced neural network is proposed for recognizing them, which has the algorithm of combining the modified ART1 and the supervised learning method. The proposed method has applied to the real-world car images. The simulation results show that the proposed method has better the extraction rates than the methods with information of the gray brightness and the RGB, respectively. And the proposed method has better recognition performance than the conventional backpropagation neural network.

• The Research Journal of the Costume Culture
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• v.13 no.6 s.59
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• pp.883-895
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• 2005

Exaggeration is to express an object or a situation in an excessive way. As the desire for aesthetic expression grows greater today, we tended to focus on the exaggerative expression as a means to acquire other's attention and praise. Also people more actively express their own intention or opinion in an exaggerated manner. The purpose of this study is to identify the social and cultural functions of modern fashion via exaggerative expression, one of the formative characteristics, and its meaning. To do so, the exaggerative features of modern fashion have been analyzed, and the social and cultural meaning of those have been examined through the background of the times and aesthetic sense. The formative form in the exaggerative expression shown in the modern fashion was classified into a body priority type emphasizing woman's body contour, a body disregarded type shown oversized silhouette regardless of body contour and a body distorted type expressing free and diverse form in various shapes of asymmetry and imbalance. The symbolic meanings of those include the changing of the body consciousness and the notions of feminity, and the desire fur formative and playable expression. The exaggeration of the costume in history meant aesthetic value of the woman's body in the society led by men. However, the exaggerative expression shown in the modern fashion is a method to express more actively, as compared with the costume in the past.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.5
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• pp.1-11
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• 2007

As the availability of an image information has been significantly increasing, necessity of system that can manage an image information is increasing. Accordingly, we proposed the region-based content retrieval(CBIR) algorithm based on an efficient combination of an image segmentation, an image texture, a color feature and an image's shape and position information. As a color feature, a HSI color histogram is chosen which is known to measure spatial of colors well. We used active contour and CWT(complex wavelet transform) to perform an image segmentation and extracting an image texture. And shape and position information are obtained using Hu invariant moments in the luminance of HSI model. For efficient similarity computation, the extracted features(color histogram, Hu invariant moments, and complex wavelet transform) are combined and then precision and recall are measured. As a experimental result using DB that was supported by www.freefoto.com. the proposed image retrieval engine have 94.8% precision, 82.7% recall and can apply successfully image retrieval system.

• Journal of Internet Computing and Services
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• v.3 no.6
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• pp.13-24
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• 2002

This paper presents an automatic approach to detect face and facial feature from face images based on the color information and deformable model. Skin color information has been widely used for face and facial feature diction since it is effective for object recognition and has less computational burden, In this paper, we propose how to compensates varying light condition and utilize the transformed YCbCr color model to detect candidates region of face and facial feature from color images, Moreover, the detected face facial feature areas are subsequently assigned to a initial condition of active contour model to extract optimal boundaries of face and facial feature by resolving initial boundary problem when the active contour is used, The experimental results show the efficiency of the proposed method, The face and facial feature information will be used for face recognition and facial feature descriptor.