• Journal of Broadcast Engineering
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• v.9 no.3
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• pp.207-213
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• 2004

The layered depth image (LDI) is an efficient approach to represent three-dimensional objects with complex geometry for image-based rendering (IBR). LDI contains several attribute values together with multiple layers at each pixel location. In this paper, we propose an efficient preprocessing algorithm to compress depth information of LDI. Considering each depth value as a point in the two-dimensional space, we compute the minimum distance between a straight line passing through the previous two values and the current depth value. Finally, the minimum distance replaces the current attribute value. The proposed algorithm reduces the variance of the depth information , therefore, It Improves the transform and coding efficiency.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.7
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• pp.37-45
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• 1998

In this paper, we extracted heart region using dyamic contour model, increased the vertical resolution of heart region by proposed 2-dimensional interpolation method and visualized the 3-dimensional hearet volutme. the proposed new energy term of dynamic contour model considering the gray level and direction of controur vectors is effective to extract the closed heart boundary. And, we generatedvertical slice images from the extracted heart region images using the 2-dimensional linear interpolation by DT(distance transform). We showed that proposed algorithm is useful by 3-dimensional visualization of heart volume.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.345-348
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• 1994

A real-time collision avoidance algorithm for an AMR (Autonomous Mobile Robot) using the Distance Transform and Vector Field Histogram is studied. This approach enables AMR to find a collision-free path with the unknown obstacles. All system parameters including positions of the obstacles can be accepted using a mouse icon and all the obtained trajectories can be displayed on a computer monitor in graphics.

• The Journal of the Acoustical Society of Korea
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• v.20 no.1
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• pp.50-55
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• 2001

This paper presents a korean isolated words recognition algorithm which used new endpoint detection method, auditory model, 2D-DCT and new distance measure. Advantages of the proposed algorithm are simple hardware construction and fast recognition time than conventional algorithms. For comparison with conventional algorithm, we used DTW method. At result, we got similar recognition rate for speaker dependent korean isolated words and better it for speaker independent korean isolated words. And recognition time of proposed algorithm was 200 times faster than DTW algorithm. Proposed algorithm had a good result in noise environments too.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.12
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• pp.1271-1280
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• 2012

In the recent parking assistant systems, finding out the distance to the object behind a car is often performed by the range sensors such as ultrasonic sensors, radars. However, the installation of additional sensors on the used vehicle could be difficult and require extra cost. On the other hand, the motion stereo technique that extracts distance information using only an image sensor was also proposed. However, In the stereo rectification step, the motion stereo requires good features and exacts matching result. In this paper, we propose a fast algorithm that extracts the accurate distance information for the parallel parking situation using the consecutive images that is acquired by a rear-view camera. The proposed algorithm uses the quadrangle transform of the image, the horizontal line integral projection, and the blocking-based correlation measurement. In the experiment with the magna parallel test sequence, the result shows that the line-accurate distance measurement with the image sequence from the rear-view camera is possible.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.7
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• pp.1024-1031
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• 2012

In this paper, FMCW type radar level transmitter using correlation analysis method is implemented for precise distance measurement of cargo tank. FMCW type radar level transmitter is the device for distance measurement which calculates the distance by analyzing the beat frequency, that is, the frequency difference between Tx and RX signal from radar antenna using Fast Fourier Transform(FFT), but compensated algorithm like Zoom FFT is needed for the improvement of the frequency precision because the frequency precision of FFT is limited depending on sampling frequency and the number of sampling data. In case of Zoom FFT, the number of sampling data and noisy signal are the main factor influencing the measurement accuracy of Zoom FFT like FFT. Therefore, in order to overcome the limited environment and achieve the precise measurement, correlation coefficient is used for the distance measurement and the errors of measurement are verified to be in the range of ${\pm}1mm$.

• Journal of Korea Multimedia Society
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• v.11 no.6
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• pp.764-776
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• 2008

Image identification is the process of checking whether the query image is the transformed version of the specific original image or not. In this paper, image identification method based on feature composition is proposed. Used features include color distance, texture information and average pixel intensity. We extract color characteristics using color distance and texture information by Modified Generalized Symmetry Transform as well as average intensity of each pixel as features. Individual feature is quantized adaptively to be used as bins of histogram. The histogram is normalized according to data type and it is used as the signature in comparing the query image with database images. In matching part, Manhattan distance is used for measuring distance between two signatures. To evaluate the performance of the proposed method, independent test and accuracy test are achieved. In independent test, 60,433 images are used to evaluate the ability of discrimination between different images. And 4,002 original images and its 29 transformed versions are used in accuracy test, which evaluate the ability that the proposed algorithm can find the original image correctly when some transforms was applied in original image. Experiment results show that the proposed identification method has good performance in accuracy test. And the proposed method is very useful in real environment because of its high accuracy and fast matching capacity.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.435-444
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• 2005

This paper presents a lane-departure identification (LDI) algorithm for a traveling vehicle on a structured road. The algorithm makes up for the weak points of the former method based on EDF[1] by introducing a Lane Boundary Pixel Extractor (LBPE), the well known Hough transform, and liner regression. As a filter to extract pixels expected to be on lane boundaries, the LBPE plays an important role in enhancing the robustness of LDI. Utilizing the pixels from the LBPE the Hough transform provides the lane-related parameters composed of orientation and distance, which are used in the LDI. The proposed LDI is based on the fact the lane-related parameters of left and right lane boundaries are symmetrical as for as the optical axis of a camera mounted on a vehicle is coincident with the center of lane; as the axis deviates from the center of lane, the symmetrical property is correspondingly lessened. In addition, the LDI exploits a linear regression of the lane-related parameters of a series of successive images. It plays the key role of determining the trend of a vehicle's traveling direction and minimizing the noise effect. Except for the two lane-related parameters, the proposed algorithm does not use other information such as lane width, a curvature, time to lane crossing, and of feet between the center of a lane and the optical axis of a camera. The system performed successfully under various degrees of illumination and on various road types.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1550-1552
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• 2005

In this paper, we have designed a Fingerprint Recognition System based on the Embedded LINUX. The fingerprint is captured using the AS-S2 semiconductor sensor. To extract a feature vector we transform the image of the fingerprint into a column vector. The image is row-wise filtered with the low-pass filter of the Haar wavelet. The feature vectors of the different fingerprints are compared by computing with the probabilistic neural network the distance between the target feature vector and the stored feature vectors in advance. The system implemented consists of a server PC based on the LINUX and a client based on the Embedded LINUX. The client is a Tynux box-x board using a PXA-255 CPU. The algorithm is simple and fast in computing and comparing the fingerprints.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.204-206
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• 2005

In this paper, we have designed a Fingerprint Recognition System based on the Embedded LINUX. The fingerprint is captured using the AS-S2 semiconductor sensor. To extract a feature vector we transform the image of t10he fingerprint into a column vector. The image is row-wise filtered with the low-pass filter of the Haar wavelet. The feature vectors of the different fingerprints are compared by computing with the probabilistic neural network the distance between the target feature vector and the stored feature vectors in advance. The system implemented consists of a server PC based on the LINUX and a client based on the Embedded LINUX. The client is a Tynux box-x board using a PXA-255 CPU. The algorithm is simple and fast in computing and comparing the fingerprints.