• Journal of Korea Multimedia Society
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• v.12 no.9
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• pp.1233-1241
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• 2009

Over the 50 percents of women who are older than 45 years have osteoporosis. Because people hardly recognize this disease by themselves, the researches that measure bone mineral density have been doing widely to detect osteoporosis in the early stage. The most widely used methods for bone mineral density measurement are based on the X-ray imaging. Among them, DEXA(Dual-energy X-ray Absorptiometry) imaging is one of the important methods in bone mineral density measurement. DEXA images are useful methods to increase diagnosis efficiency by reducing anatomic noise as two images obtained from two different energy levels. However, it has some problems to a calibration parameter determined by the heuristic method for bone extraction. In this paper, we propose the method to extract bone in DEXA image using calibration parameter based on anatomic attenuation coefficient. The experimental results reveal that the proposed method is effective.

• The KIPS Transactions:PartB
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• v.15B no.2
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• pp.123-130
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• 2008

Automatic lipreading is to recognize speech by observing the movement of a speaker's lips. It has received attention recently as a method of complementing performance degradation of acoustic speech recognition in acoustically noisy environments. One of the important issues in automatic lipreading is to define and extract salient features from the recorded images. In this paper, we propose a feature extraction method by using a new filtering technique for obtaining improved recognition performance. The proposed method eliminates frequency components which are too slow or too fast compared to the relevant speech information by applying a band-pass filter to the temporal trajectory of each pixel in the images containing the lip region and, then, features are extracted by principal component analysis. We show that the proposed method produces improved performance in both clean and visually noisy conditions via speaker-independent recognition experiments.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1615-1623
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• 2008

This paper proposes methods to classify scanned insect footprints. We propose improved SOM and ART2 algorithms for extracting segments, basic areas for feature extraction, and utilize Trace transform and fuzzy weighted mean methods for extracting feature values for classification of the footprints. In the proposed method, regions are extracted by a morphological method in the beginning, and then improved SOM and ART2 algorithms are utilized to extract segments regardless of kinds of insects. Next, A Trace transform method is used to find feature values suitable for various kinds of deformation of insect footprints. In the Trace transform method, Triple features from reconstructed combination of diverse functions, are used to classify the footprints. In general, it is very difficult to decide automatically whether the extracted footprint segment is meaningful for classification or not. So we use a fuzzy weighted mean method for not excluding uncertain footprint segments because the uncertain footprint segments may be possible candidates for classification. We present experimental results of footprint segment extraction and segment classification by the proposed methods.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.503-512
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• 2007

An infant of a baby child who haven't communication skills through a language expresses their intention or baby condition as generally crying. Among these things, it is important to show a baby condition because their disease miss diagnosis time or remain to decide an exact diagnosis result too hard. For this, in this paper, we are going to develop system which decides where to be not good body point by analysing their face color and crying sound. Specifically, in this paper, we are going to act for baby heart diseases by doing feature extraction for their face region color and crying sound. To embody, we are going to present diagnosis method and compare analyze their crying sound a stand child, a different diseases child and a baby heart diseases child through each analyzed element. And also, we are going to extract matters to be attended to baby heart diseases through experiment and prepare objective index and an accuracy of baby heart diseases diagnosis result.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.506-511
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• 2004

Biometrics is getting more and more attention in recent years for security and other concerns. So far, only fingerprint recognition has seen limited success for on-line security check, since other biometrics verification and identification systems require more complicated and expensive acquisition interfaces and recognition processes. Hand-Geometry has been used for biometric verification and identification because of its acquisition convenience and good performance for verification and identification performance. Hence, it can be a good candidate for online checks. Therefore, this paper proposes a Hand-Geometry recognition system based on geometrical features of hand. From anatomical point of view, human hand can be characterized by its length, width, thickness, geometrical composition, shapes of the palm, and shape and geometry of the fingers. This paper proposes thirty relevant features for a Hand-Geometry recognition system. However, during experimentation, it was discovered that length measured from the tip of the finger was not a reliable feature. Hence, we propose a new technique based on Genetic Algorithm for extraction of the center of nail bottom, in order to use it for the length feature.

• Journal of Broadcast Engineering
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• v.20 no.5
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• pp.728-737
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• 2015

Stitching algorithm obtain a descriptor of the feature points extracted from multiple images, and create a single image through the matching process between the each of the feature points. In this paper, a feature extraction and matching techniques for the creation of a high-speed panorama using video input is proposed. Features from Accelerated Segment Test(FAST) is used for the feature extraction at high speed. A new feature point matching process, different from the conventional method is proposed. In the matching process, by tracking region containing the feature point through the Mean shift vector required for matching is obtained. Obtained vector is used to match the extracted feature points. In order to remove the outlier, the RANdom Sample Consensus(RANSAC) method is used. By obtaining a homography transformation matrix of the two input images, a single panoramic image is generated. Through experimental results, we show that the proposed algorithm improve of speed panoramic image generation compared to than the existing method.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.247-256
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• 2005

One of the classic research problems in computer vision is that of stereo, i.e., the reconstruction of three dimensional shape from two or more images. This paper deals with the problem of extracting depth information of non-rigid dynamic 3D scenes from general 2D video sequences taken by monocular camera, such as movies, documentaries, and dramas. Depth of the blocks are extracted from the resultant block motions throughout following two steps: (i) calculation of global parameters concerned with camera translations and focal length using the locations of blocks and their motions, (ii) calculation of each block depth relative to average image depth using the global parameters and the location of the block and its motion, Both singular and non-singular cases are experimented with various video sequences. The resultant relative depths and ego-motion object shapes are virtually identical to human vision.

• Korean Chemical Engineering Research
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• v.47 no.3
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• pp.281-286
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• 2009

Bitumen extraction and sulfur removal from Athabasca oil sand were conducted using water in sub- and supercritical condition. Bitumen yield in micro reactor was investigated in the pressure range of 15~30 MPa, the temperature of 360 and $380^{\circ}C$ and water density $0.074{\sim}0.61g/cm^3$ for 0~120 min. Bitumen yield increased with reaction pressure irrespective of temperature and dramatically increased in especially supercritical region due to hydrogen formed from water gas shift reaction. Total amount of gas product decreased with reaction pressure but the portion of sulfur and hydrogen increased a little with increasing pressure to 25 and 30 MPa. It is seen that supercritical condition was favourable to the hydrogen formation and sulfur removal. Bitumen yield and sulfur removal from original oil sand reached a maximum 22% and 40% respectively in supercritical condition(the reaction time of 60 min at $380^{\circ}C$ and 25 or 30 MPa).

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.1113-1118
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• 2002

In recognition system of the car license plate, the most important is to extract the image of the license plate from a car image. In this paper, we use ACL (Adaptive Color Luminance) algorithm to extract the license plate image from a car image. The ACL algorithm that uses color and luminance information of a car image is used to extract the image of the license plate. In this paper, color, luminance and other related information of a car image are used to extract the image of the license plate from that of a car. In this reason, we call it the ACL algorithm. The ACL algorithm uses color, luminance information and other related information of a license plate. These informations are avaliable to exact the image of the license plate. The rate of extracting the image of the license plate from a car is 97%. The experimental result of the ACL algorithm for the character region is 92%.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.4
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• pp.293-300
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• 2013

Road signs are important infrastructures for safe and smooth traffic by providing useful information to drivers. It is necessary to establish road sign DB for managing road signs systematically. To provide such DB, manually detection and recognition from imagery can be done. However, it is time and cost consuming. In this study, we proposed algorithms for automatic recognition of direction information in road sign image. Also we developed algorithm code using OpenCV library, and applied it to road sign image. To automatically detect and recognize direction information, we developed program which is composed of various modules such as image enhancement, image binarization, arrow region extraction, interesting point extraction, and template image matching. As a result, we can confirm the possibility of automatic recognition of direction information in road sign image.