• Journal of the Korean Society of Radiology
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• v.9 no.3
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• pp.139-145
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• 2015

When examining a patient using SPECT, gamma rays emitted from the body decrease or scatter. And when they reach the detector they spread in accordance with physical characteristics and geometric shapes of the scanner, quantitative analysis was difficult. For exact quantitative analysis of gamma rays emitted from the body, so that they must be considered to correction about PVE(partial volume effect). In this paper, sinogram filter was implemented to solve comprehensive PVE of SPECT. According to the results in which implemented filter was applied, partial volume effect caused by SPECT was removed. To compare proposed method and conventional method, PSNR(Peak Signal to Noise Ratio) was executed. As a result, proposed method was indicated as 7dB, conventional method was indicated as 14db respectively. dB(decibel) level of the proposed methods is lower, since the MSE(mean square error) becomes greater because scattered ray was removed, PSNR value is low. Therefore, by applying the proposed method for removing the PVE of SPECT imaging method, the image quality is improved.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.9
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• pp.848-857
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• 2011

Vision-based collision avoidance system for air traffic management requires a excellent multiple target detection algorithm under low signal-to-noise ratio (SNR) levels. The track-before-detect (TBD) approaches have significant applications such as detection of small and dim targets from an image sequence. In this paper, two detection algorithms with the TBD approaches are proposed to satisfy the multiple target detection requirements. The first algorithm, based on a dynamic programming approach, is designed to classify multiple targets by using a k-means clustering algorithm. In the second approach, a hidden Markov model (HMM) is slightly modified for detecting multiple targets sequentially. Both of the proposed approaches are used in numerical simulations with variations in target appearance properties to provide satisfactory performance as multiple target detection methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3955-3971
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• 2020

Due to the significant increase in the use of autonomous car technology, it is essential to integrate this technology with high-precision digital map data containing more precise and accurate roadway information, as compared to existing conventional map resources, to ensure the safety of self-driving operations. While existing map technologies may assist vehicles in identifying their locations via Global Positioning System, it is however difficult to update the environmental changes of roadways in these maps. Roadway vision algorithms can be useful for building autonomous vehicles that can avoid accidents and detect real-time location changes. We incorporate a hybrid architectural design that combines unsupervised classification of vision data with supervised joint fusion classification to achieve a better noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid fusion algorithm for fusing multimodal vision feature data for roadway classifications and characterize its improvement in accuracy over unsupervised identifications using image processing and supervised vision classifiers. We analyzed over 93,000 vision frame data collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.55-62
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• 2013

This paper aims to detect Speed Bump by using Omni-directional Camera and to suggest Real-time update scheme of Speed Bump through Vision Based Approach. In order to detect Speed Bump from sequence of camera images, noise should be removed as well as spot estimated as shape and pattern for speed bump should be detected first. Now that speed bump has a regular form of white and yellow area, we extracted speed bump on the road by applying erosion and dilation morphological operations and by using the HSV color model. By collecting huge panoramic images from the camera, we are able to detect the target object and to calculate the distance through GPS log data. Last but not least, we evaluated accuracy of obtained result and detection algorithm by implementing SLAMS (Simultaneous Localization and Mapping system).

• Journal of Broadcast Engineering
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• v.18 no.6
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• pp.850-858
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• 2013

In this paper, we propose a method of frame synchronization for stereoscopic 3D video to solve the viewing problem caused by synchronization errors between a left video and a right video using the temporal frame difference image depending on the movement of objects. Firstly, we compute two temporal frame difference images from the left video and the right video which are corrected the vertical parallax between two videos using rectification, and calculate two horizontal projection profiles of two temporal frame difference images. Then, we find a pair of synchronized frames of the two videos by measuring the mean of absolute difference (MAD) of two horizontal projection profiles. Experimental results show that the proposed method can be used for stereoscopic 3D video, and is robust against Gaussian noise and video compression by H.264/AVC.

• Journal of Biomedical Engineering Research
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• v.16 no.4
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• pp.425-430
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• 1995

The correlation technique has been widely used in ctRl data processing. The proposed CLT (clus- tering threshold) technique is a modified CCT (correlation coefficient threshold) technique and has many advantages compared with the conventional CCT technique. The CLT technique is explained by the following two steps. First, once the correlation coefficient map above the proper TH value is obtained using the CCT technique which is discrete and includes splash noise data, then the spurious pixels are rejected and the real neural activity pixels extracted using an nxn matrix box. Second, a clustering operation is performed by the two correction rules. The real neuronal activated pixels can be clustered and the false spurious pixels can be suppressed by the proposed CLT technique. The proposed CLT technique used in the post processing in ctRl has advantages over other existing techniques. It is especially proved to be robust in noisy environment.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.11a
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• pp.416-419
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• 2002

There are being two prominent studying for Digital Radiography. Direct and Indirect method of Digital Radiography are announced for producing high quality digital image. The one is using amorphous selenium as photoconductor and the other is using phosphor layer as a light conversion. But each two systems have strength and weakness such as high voltage and blurring effect. In this study, we investigated the electrical characteristic of $multi-layer\left(CaWO_{4}+a-Se \right)$ as a photoconductor according to the changing arsenic composition ratio. This is a basic research for developing of Hybrid digital radiography which is a new type X-ray detector. The arsenic composition ratio of a-Se compound is classified into 7 different kinds which have 0.1%, 0.3%, 0.5%, 1%, 1.5%, 5%, 10% and were made test sample throught thermo-evaporation. The phosphor layer of $CaWO_4$ was overlapped on a-Se using EFIRON optical adhesives. We measured the dark and photo current about the test sample and compared the electrical characteristic of the net charge and signal-to-noise ratio. Among other things, test sample of compound material of 0.3% arsenic showed good characteristic of $2.45nA/cm^2$ dark current and $357.19pC/cm^2/mR$ net charge at $3V/{\mu}m$.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.295-298
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• 2003

In this paper, a novel maximum a posterion (MAP) estimation for the channel decoding of H.264 codes in the presence of transmission error is presented. Arithmetic codes with a forbidden symbol and trellis search techniques are employed in order to estimate the best transmitted. And, there has been growing interest of communication, the research about transmission of exact data is increasing. Unlike the case of voice transmission, noise has a fatal effect on the image transmission. The reason is that video coding standards have used the variable length coding. So, only one bit error affects the all video data compressed before resynchronization. For reasons of that, channel needs the channel codec, which is robust to channel error. But, usual channel decoder corrects the error only by channel error probability. So, designing source codec and channel codec, Instead of separating them, it is tried to combine them jointly. And many researches used the information of source redundancy In received data. But, these methods do not match to the video coding standards, because video ceding standards use not only one symbol but also many symbols in same data sequence. In this thesis, We try to design combined source-channel codec that is compatible with video coding standards. This MAP decoder is proposed by adding semantic structure and semantic constraint of video coding standards to the method using redundancy of the MAP decoders proposed previously. Then, We get the better performance than usual channel coder's.

• Journal of Digital Contents Society
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• v.16 no.1
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• pp.157-164
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• 2015

The existing input device is limited to keyboard and mouse. However, recently new type of input device has been developed in response to requests from users. To reflect this trend we propose the new type of input device that gives instruction as analyzing the hand motion of image without special device. After binarizing the skin color area using Cam-Shift method and tracking, it recognizes the hand motion by inputting the finger areas and the angles from the palm center point, which are separated through labeling, into four cardinal directions and counting them. In cases when specific background was not set and without gloves, the recognition rate remained approximately at 75 percent. However, when specific background was set and the person wore red gloves, the recognition rate increased to 90.2 percent due to reduction in noise.

• Journal of Digital Contents Society
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• v.15 no.6
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• pp.675-682
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• 2014

Prostate is only an organ of men. To diagnose the disease of the prostate, generally transrectal ultrasound(TRUS) images are used. Detecting its boundary is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a method for automatic prostate segmentation in TRUS images using Support Vector Machine(SVM) is presented. This method involves preprocessing, extracting Gabor feature, training, and prostate segmentation. The speckle reduction for preprocessing step has been achieved by using stick filter and top-hat transform has been implemented for smoothing. Gabor filter bank for extraction of rotation-invariant texture features has been implemented. SVM for training step has been used to get each feature of prostate and nonprostate. Finally, the boundary of prostate is extracted. A number of experiments are conducted to validate this method and results shows that the proposed algorithm extracted the prostate boundary with less than 10% relative to boundary provided manually by doctors.