• Journal of information and communication convergence engineering
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• v.12 no.3
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• pp.168-172
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• 2014

In this paper, we propose an algorithm that can efficiently detect and monitor multiple ships in real-time. The proposed algorithm uses morphological operations and edge information for detecting and tracking ships. We used smoothing filter with a $3{\times}3$ Gaussian window and luminance component instead of RGB components in the captured image. Additionally, we applied Sobel operator for edge detection and a threshold for binary images. Finally, object labeling with connectivity and morphological operation with open and erosion were used for ship detection. Compared with conventional methods, the proposed method is meant to be used mainly in coastal surveillance systems and monitoring systems of harbors. A system based on this method was tested for both stationary and non-stationary backgrounds, and the results of the detection and tracking rates were more than 97% on average. Thousands of image frames and 20 different video sequences in both online and offline modes were tested, and an overall detection rate of 97.6% was achieved.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.1425-1432
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• 2010

In large construction site, although soil conversion factor is so significant to preliminary design, operation design and calculating the cost of construction that it is important to take reasonable estimation and application, the standard of soil conversion factor for weathered ground doesn't clearly suggested yet. So in this study, at first we obtain the image using DSLR - high resolution camera and Laser scanner in the Haeng-Bok city constructin site, then analysis the ratio of soil and rock using various image processing method(Sobel method, Laplace method, Highpass filter, Hue and Saturation analysis). Mutual comparation with the result of image processing analysis and manual segmentation of 5case image in the cad. As a result, best image processing method was different for each case. In case of high propotion of rock, Laplace was best and in case of high propotion of soil, Highpass was best, and mixed case Laplace was best.

• Journal of IKEEE
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• v.16 no.4
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• pp.310-315
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• 2012

This thesis is intended to design multi thread mobile GPGPU optimized in mobile environment, and to verify an effective thread management method of the multi thread mobile processor. In thread management, there is no management hardware and implement with software instructions. For the verification of the multi thread management method, Lane detection algorithm was implemented to compare nVidia's CUDA Architecture and the designed GPGPU in terms of thread management efficiency. The number of thread is normalized to 48 threads. An implemented Land Detection Algorithm is composed of Gaussian filter algorithm and Sobel Edge Detection algorithm. As a result, the designed GPGPU's thread efficiency is up to 2 times higher than CUDA's thread efficiency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.313-318
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• 2006

본 논문에서는 ART-1 기반 자가 생성 지도학습 알고리즘과 얼굴 인증을 이용한 주민등록증 인식방법을 제안한다. 본 논문에서는 주민등록증 영상에서 주민등록번호와 발행일을 추출하기 위해, 획득된 주민등록증의 영상에서 Sobel Mask와 Median Filter를 이용하여 윤곽선을 추출하고 잡음을 제거한 후, 수평 스미어링을 적용하여 주민등록번호와 발행일 영역을 각각 추출한다. 그리고 고주파 필터링을 적용하여 추출된 영역을 이진화하고 4방향 윤곽선 추적 알고리즘을 적용하여 개별 코드를 추출한다. 추출된 개별 코드는 ART-1 기반 자가 생성 지도학습 알고리즘을 적용하여 인식한다. 얼굴 인증은 Template Matching 방법을 적용하여 Face Template Database를 구축하고, 획득된 주민등록증의 얼굴 영역과의 유사도를 측정하여 주민등록증의 사진 위조 여부를 판별한다. 제안된 주민등록증 인식 방법의 성능을 평가하기 위해 10개의 주민등록증을 대상으로 실험하였고 원본 주민등록증 영상에서 사진과 얼굴 부분을 위조한 주민등록증에 대해 얼굴 인증 실험을 하였다. 실험을 통해 제안된 방법이 주민등록번호 인식 및 얼굴 인증에 있어서 우수한 성능이 있음을 확인하였다.

• Journal of the Korea Society for Simulation
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• v.27 no.2
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• pp.1-10
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• 2018

This paper presents an autonomous detection and aiming point computation of a battle tank by using RGB images. Maximally stable extremal regions algorithm was implemented to find features of the tank, which are matched with images extracted from streaming video to figure out the region of interest where the tank is present. The median filter was applied to remove noises in the region of interest and decrease camouflage effects of the tank. For the tank segmentation, k-mean clustering was used to autonomously distinguish the tank from its background. Also, both erosion and dilation algorithms of morphology techniques were applied to extract the tank shape without noises and generate the binary image with 1 for the tank and 0 for the background. After that, Sobel's edge detection was used to measure the outline of the tank by which the aiming point at the center of the tank was calculated. For performance measurement, accuracy, precision, recall, and F-measure were analyzed by confusion matrix, resulting in 91.6%, 90.4%, 85.8%, and 88.1%, respectively.

• Journal of radiological science and technology
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• v.45 no.2
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• pp.145-150
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• 2022

The main purpose of this work was to restore the blurry chest CT images by applying a blind deconvolution algorithm. In general, image restoration is the procedure of improving the degraded image to get the true or original image. In this regard, we focused on a blind deblurring approach with chest CT imaging by using digital image processing in MATLAB, which the blind deconvolution technique performed without any whole knowledge or information as to the fundamental point spread function (PSF). For our approach, we acquired 30 chest CT images from the public source and applied three type's PSFs for finding the true image and the original PSF. The observed image might be convolved with an isotropic gaussian PSF or motion blurring PSF and the original image. The PSFs are assumed as a black box, hence restoring the image is called blind deconvolution. For the 30 iteration times, we analyzed diverse sizes of the PSF and tried to approximate the true PSF and the original image. For improving the ringing effect, we employed the weighted function by using the sobel filter. The results was compared with the three criteria including mean squared error (MSE), root mean squared error (RMSE) and peak signal-to-noise ratio (PSNR), which all values of the optimal-sized image outperformed those that the other reconstructed two-sized images. Therefore, we improved the blurring chest CT image by using the blind deconvolutin algorithm for optimal approach.

• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.764-781
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• 2013

In this paper, we propose a highly precise vehicle detection method with low false alarm using billboard sweep stereo matching and multi-stage hypothesis generation. First, we capture stereo images from cameras established in front of the vehicle and obtain the disparity map in which the regions of ground plane or background are removed using billboard sweep stereo matching algorithm. And then, we perform the vehicle detection and tracking on the labeled disparity map. The vehicle detection and tracking consists of three steps. In the learning step, the SVM(support vector machine) classifier is obtained using the features extracted from the gabor filter. The second step is the vehicle detection which performs the sobel edge detection in the image of the left camera and extracts candidates of the vehicle using edge image and billboard sweep stereo disparity map. The final step is the vehicle tracking using template matching in the next frame. Removal process of the tracking regions improves the system performance in the candidate region of the vehicle on the succeeding frames.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.2
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• pp.65-77
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• 2009

This paper proposes fast image processing algorithms using SSE (Streaming SIMD Extensions) instructions. The CPU's supporting SSE instructions have 128bit XMM registers; data included in these registers are processed at the same time with the SIMD (Single Instruction Multiple Data) mode. This paper develops new SIMD image processing algorithms for Mean filter, Sobel horizontal edge detector, and Morphological erosion operation which are most widely used in automated optical inspection systems and compares their processing times. In order to objectively evaluate the processing time, the developed algorithms are compared with OpenCV 1.0 operated in SISD (Single Instruction Single Data) mode, Intel's IPP 5.2 and MIL 8.0 which are fast image processing libraries supporting SIMD mode. The experimental result shows that the proposed algorithms on average are 8 times faster than the SISD mode image processing library and 1.4 times faster than the SIMD fast image processing libraries. The proposed algorithms demonstrate their applicability to practical image processing systems at high speed without commercial image processing libraries or additional hardwares.

• Journal of Intelligence and Information Systems
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• v.12 no.1
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• pp.1-15
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• 2006

In Korea, a resident registration card has various personal information such as a present address, a resident registration number, a face picture and a fingerprint. A plastic-type resident card currently used is easy to forge or alter and tricks of forgery grow to be high-degree as time goes on. So, whether a resident card is forged or not is difficult to judge by only an examination with the naked eye. This paper proposed an automatic recognition method of a resident card which recognizes a resident registration number by using a refined ART2-based RBF network newly proposed and authenticates a face picture by a template image matching method. The proposed method, first, extracts areas including a resident registration number and the date of issue from a resident card image by applying Sobel masking, median filtering and horizontal smearing operations to the image in turn. To improve the extraction of individual codes from extracted areas, the original image is binarized by using a high-frequency passing filter and CDM masking is applied to the binaried image fur making image information of individual codes better. Lastly, individual codes, which are targets of recognition, are extracted by applying 4-directional contour tracking algorithm to extracted areas in the binarized image. And this paper proposed a refined ART2-based RBF network to recognize individual codes, which applies ART2 as the loaming structure of the middle layer and dynamicaly adjusts a teaming rate in the teaming of the middle and the output layers by using a fuzzy control method to improve the performance of teaming. Also, for the precise judgement of forgey of a resident card, the proposed method supports a face authentication by using a face template database and a template image matching method. For performance evaluation of the proposed method, this paper maked metamorphoses of an original image of resident card such as a forgey of face picture, an addition of noise, variations of contrast variations of intensity and image blurring, and applied these images with original images to experiments. The results of experiment showed that the proposed method is excellent in the recognition of individual codes and the face authentication fur the automatic recognition of a resident card.