• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.6
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• pp.10-21
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• 2000

The Cellular Noninear Networks structure for Distance Transform(DT) and the robust optical flow detection algorithm based on the DT are proposed. For some applications of optical flows such as target tracking and camera ego-motion computation, correct optical flows at a few feature points are more useful than unreliable one at every pixel point. The proposed algorithm is for detecting the optical flows on the trajectories only of the feature points. The translation lengths and the directions of feature movements are detected on the trajectories of feature points on which Distance Transform Field is developed. The robustness caused from the use of the Distance Transform and the easiness of hardware implementation with local analog circuits are the properties of the proposed structure. To verify the performance of the proposed structure and the algorithm, simulation has been done about various images under different noisy environment.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.5
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• pp.163-167
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• 2016

We have developed a millimeter-wave radiometer system for applications in the fields of medical imaging. In this paper, we introduced the brightness temperature measurement in the human body using Millimeter-wave Radiometer. Calibration of sensitivity of the radiometer system is essential to measure equivalent temperature (brightness temperature) of objects. We have developed, as a calibration source, a new type of black body for the millimeter wave region with temperature control capability. The system noise figure and temperature sensitivity of the system measured using the blackbody are 3.3 dB and 0.1 K, respectively. The brightness temperature of human body through clothes was measured to be around $38^{\circ}$[C].

• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.167-177
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• 2013

In this paper, a motion adaptive deinterlacing algorithm is proposed. It consists of three parts: (1) modified edge-based line average, (2) pixel-based consequent five-field motion detection, and (3) block-based local characteristic for detecting true motion and calculating the motion intensity by using an improved method which is able to detect the inner part of moving objects precisely as well as to reduce the risk of false detection caused by intrinsic noises in the image. Depending on the detected motion activity level, it combines spatial and temporal methods with weighting factor. Simulations conducted on several video sequences indicate that the performance of the proposed method is superior to the conventional methods in terms of both subjective and objective video quality.

• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.185-195
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• 2013

In this paper, we propose a video summarization technique on a smartphone, based on spatiotemporal saliency. The proposed technique detects scene changes by computing the difference of the color histogram, which is robust to camera and object motion. Then the similarity between adjacent frames, face region, and frame saliency are computed to analyze the spatiotemporal saliency in a video clip. Over-segmented hierarchical tree is created using scene changes and is updated iteratively using mergence and maintenance energies computed during the analysis procedure. In the updated hierarchical tree, segmented frames are extracted by applying a greedy algorithm on the node with high saliency when it satisfies the reduction ratio and the minimum interval requested by the user. Experimental result shows that the proposed method summaries a 2 minute-length video in about 10 seconds on a commercial smartphone. The summarization quality is superior to the commercial video editing software, Muvee.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.29-36
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• 2012

In this paper, we suggest a new method of detecting human skin-color regions from three-dimensional static or dynamic stereoscopic images by effectively integrating depth and color features. The suggested method first extracts depth information that represents the distance between a camera and an object from input left and right stereoscopic images through a stereo matching technique. It then performs labeling for pixels with similar depth features and determines the labeled regions having human skin color as actual skin color regions. Our experimental results show that the suggested skin region extraction method outperforms existing skin detection methods in terms of skin-color region extraction accuracy.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.190-200
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• 2014

The video-based system of the broadcasters and the video-related institutions have shifted from analogical to digital in worldwide. This migration process can generate a defect, digital dropout, in the quality of the contents. Moreover, there are limited researches focused on these kind of defects and those related have limitations. For that reason, we are proposing a new method for feature extraction emphasizing in the peculiar block pattern of digital dropout based on discrete cosine transform (DCT). For classification of error block, we utilize support vector machine (SVM) which can manage feature vectors efficiently. Further, the proposed method overcome the limitation of the previous one using continuity of frame by frame. It is using only the information of a single frame and works better even in the presence of fast moving objects, without the necessity of specific model or parameter estimation. Therefore, this approach is capable of detecting digital dropout only with minimal complexity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1925-1936
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• 2010

In this paper, multi-legged robot was designed and produced using stable walking pattern algorithm. The robot had embedded camera and wireless communication function and it is possible to recognize both hand posture and obstacles. The algorithm decided moving paths, and recognized and avoided obstacles through Hough Transform using Edge Detection of inputed image from image sensor. The robot can be controlled by hand posture using Mahalanobis Distance and average value of skin's color pixel, which is previously learned in order to decide the destination. The developed system has shown obstacle detection rate of 96% and hand posture recognition rate of 94%.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.2 s.233
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• pp.188-200
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• 2005

Control of a multi-fingered robotic hand is usually based on the theoretical analysis for kinematics and dynamics of fingers and of object. However, the implementation of such analyses to robotic hands is difficult because of errors and uncertainties in the real situations. This article presents the control method for estimating the kinematic constraint of an unknown object by active sensing. The experimental system has a two-fingered robotic hand suspended vertically for manipulation in the vertical plane. The fingers with three degrees-of-freedom are driven by wires directly connected to voice-coil motors without reduction gears. The fingers are equipped with three-axis force sensors and with dynamic tactile sensors that detect slippage between the fingertip surfaces and the object. In order to make an accurate estimation for the kinematic constraint of the unknown object, i.e. the constraint direction and the constraint center, four kinds of the active sensing and feedback control algorithm were developed: two position-based algorithms and two force-based algorithms. Furthermore, the compound and effective algorithm was also developed by combining two algorithms. Force sensors are mainly used to adapt errors and uncertainties encountered during the constraint estimation. Several experimental results involving the motion of lifting a finger off an unknown object are presented.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.1
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• pp.75-85
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• 1985

We have studied on the 2-D moving target tracking algorithm satisfying a real-time hardware implementation requirement. In this paper, a fast algorithm is developed based on the operator formulation and the variational algorithm f 10] . Here, we use the directed search for the maximum of the cross-correlation in order to obtain an initial estimate for the variational algorithm and decompose the scene into 16 smaller subblocks and apply the variational algorithm to each subblock sequentially with a new moving area detection method. We call the algorithm subblock based recursive algorithm. Compared with (10) , the ratio of the computational savings obtained from the proposed algorithm is 7 on the average.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.93-98
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• 2011

In this paper, we propose a game type cognitive rehabilitation system using marker-based augmented reality system for intelligence development of user. Existing cognitive rehabilitation with the help of others, or a keyboard or mouse operation required to relieve the discomfort, the marker card only control it led and is advanced the method which it applied. As a result, obtained through the camera calibration for image processing, and a Augmented Reality as well as mark detection. In this paper we presented a complete rotation of the model after checking through the whole form, through a combination of multiple markers by completing the interactive objects proceed with the rehabilitation process in a manner required by the target of interest to human rehabilitation and treatment.