• Journal of the Korea Society of Computer and Information
• /
• v.17 no.5
• /
• pp.29-32
• /
• 2012

In this paper, we propose a novel method to extract muscle area from lumbar ultrasonographic image. The muscle area resided in lumbar area can be defined as the area between thoracic vertebra and subcutaneous fat area. A modified 4-directional contour tracing algorithm is designed to detect the boundaries and candidate areas are extracted and verified by the morphological characteristics of lumbar area. The experiment using 392 lumbar images verifies that the proposed method is sufficiently effective by showing over 94% accuracy in extraction.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.23 no.3
• /
• pp.313-322
• /
• 2005

Rapid advances in technology and changes in human and cultural activities bring about changes to the earth surface in terms of spatial extension as well as time frame of the changes. Such advances introduce shorter updating frequency of maps and geospatial database. To satisfy these requirements, recent research efforts in the geoinformatics field have been focused on the automation and speeding up of the mapping processes which resulted in products such as the digital photogrammetric workstation, GPSIINS, applications of satellite imagery, automatic feature extraction and the LiDAR system. The possibility of automatically extracting buildings and generating contours from airborne LiDAR data has received much attention because LiDAR data produce promising results. However, compared with the manually derived building footprints using traditional photogrammetric process, more investigation and analysis need to be carried out in terms of accuracy and efficiency. On the other hand, generation of the contours with LiDAR data is more efficient and economical in terms of the quality and accuracy. In this study, the effects of various conditions of the pre-processing phase and the subsequent building extraction and contour generation phases for digital mapping have on the accuracy were investigated.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.6 no.4
• /
• pp.269-278
• /
• 2004

Recently, critical velocity has become a topic to attract most interests from the researchers in the field of tunnel safety. As the minimum velocity to prevent smoke backlayering during a fire, many equations have been proposed so far, and the following three equations are being considered as a standard method in Korea to calculate the capacity of smoke extraction fans. Equation by Kennedy based on Froude number, Tetzner' s equation with additional variable, ${\beta}$ to modify the Kennedy's equation, and the equation with the concept of super critical velocity by Wu are studied in this paper for the comparative purpose. A contour map describing the relationship between the critical velocity and the capacity of smoke extraction fans is proposed as a tool to calculate the number of jet fans for smoke control during a fire in the local tunnels.

• Journal of Korea Multimedia Society
• /
• v.11 no.1
• /
• pp.34-43
• /
• 2008

This paper presents a system for recognizing sunglasses and a mask of an ATM (Automatic Teller Machine) user. The proposed system extracts firstly facial contour, then from this extraction results it estimates the regions of eyes and mouth. Finally, it recognizes sunglasses and a mouth using Histogram Indexing based on those regions. We adopt a face shape model to be able to extract facial contour and to estimate the regions of eyes and mouth when those regions are occluded by sunglasses and a mask. To improve the fitting accuracy of the shame model, we adopt 2-step face detection method and conduct fitting several times by varying the initial position of the model instance. To achieve a good performance of the face detection method based on a background model, we enable the system to automatically update the background model. In experiment, we present some experiments on setting parameters of the system with images taken from in our laboratory, and demonstrate the results of recognizing sunglasses and a mask.

• Journal of Digital Contents Society
• /
• v.10 no.3
• /
• pp.381-388
• /
• 2009

This paper proposes a denoising method for the contour edges and crease edges of silhouette obtained from 3D scanned data of stone cultural heritages. It is often the case that the silhouette involves noise in the form of short-length line segments, due to rough surfaces of stone cultural heritages, weathering, and technical difficulties arising in data acquisition. Thus the removal of the short-length line segments from the contour edges and crease edges can result in a clear and accurate silhouette. An efficient computational algorithm is introduced to count the continuity of line segments; edges having not more than 3 line segments are removed. It has been verified that the new method is more effective than threshold-based silhouette extraction methods for stone heritages. Our method is applicable for various other data which are deteriorated by short-length line segments.

• The KIPS Transactions:PartB
• /
• v.11B no.3
• /
• pp.281-288
• /
• 2004

In order to extract and analyze complex features of the behavior of animals in response to external stimuli such as toxic chemicals, we implemented an adaptive computational method to characterize changes in the behavior of chironomids in response to treatment with the insecticide, diazinon. In this paper, we propose an energy minimization model to extract the features of response behavior of chironomids under toxic treatment, which is applied on the image of velocity vectors. It is based on the improved active contour model and the variations of the energy functional, which are produced by the evolving active contour. The movement tracks of individual chironomid larvae were continuously measured in 0.25 second intervals during the survey period of 4 days before and after the treatment. Velocity on each sample track at 0.25 second intervals was collected in 15-20 minute periods and was subsequently checked to effectively reveal behavioral states of the specimens tested. Active contour was formed around each collection of velocities to gradually evolve to find the optimal boundaries of velocity collections through processes of energy minimization. The active contour which is improved by T. Chan and L. Vese is used in this paper. The energy minimization model effectively revealed characteristic patterns of behavior for the treatment versus no treatment, and identified changes in behavioral states .is the time progressed.

• Journal of Broadcast Engineering
• /
• v.15 no.4
• /
• pp.474-486
• /
• 2010

In this paper, we propose a new method for detection moving object contour using spatial and temporal edge. In general, contour pixels of the moving object are likely present around pixels with high gradient value along the time axis and the spatial axis. Therefore, we can detect the contour of the moving objects by finding pixels which have high gradient value in the time axis and spatial axis. In this paper, we introduce a new computation method, termed as temporal edge, to compute an gradient value along the time axis for any pixel on an image. The temporal edge can be computed using two input gray images at time t and t-2 using the Sobel operator. Temporal edge is utilized to detect a candidate region of the moving object contour and then the detected candidate region is used to extract spatial edge information. The final contour of the moving object is detected using the combination of these two edge information, which are temporal edge and spatial edge, and then the post processing such as a morphological operation and a background edge removing procedure are applied to remove noise regions. The complexity of the proposed method is very low because it dose not use any background scene and high complex operation, therefore it can be applied to real-time applications. Experimental results show that the proposed method outperforms the conventional contour extraction methods in term of processing effort and a ghost effect which is occurred in the case of entropy method.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.11 no.3
• /
• pp.136-150
• /
• 2008

Many studies have been carried out for automatic extraction of building by LiDAR data or airphoto. Combining the benefits of 3D location information data and shape information data of image can improve the accuracy. So, in this research building recognition algorithm based on contour was used to improve accuracy of building recognition by LiDAR data and elaborate building boundary recognition by airphoto. Building recognition algorithm based on contour can generate building boundary and roof structure information. Also it shows better accuracy of building detection than the existing recognition methods based on TIN or NDSM. Out of creating buffers in regular size on the building boundary which is presumed by contour, this research limits the boundary area of airphoto and elaborate building boundary to fit into edge of airphoto by double active contour. From the result of this research, 3D building boundary will be able to be detected by optimal matching on the constant range of extracted boundary in the future.

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

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