• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.1
• /
• pp.105-113
• /
• 1998

A new image processor is implemented for high-speed digital copiers and facsimiles. The imgage processor performs CCD and CIS interface, pre-processing, enlargement andreduction of gray level image, and various halftoning algorithms. Implemented halftoning algorithms are simple thresholding, fuzzy based mixed mode thresholding, dithering, and edge enhanced error diffusion. The result of binarization is transferred to a printer with serial or paralel output ports. Line by line pipelined data prodessing architecture is employed with time sharing access of the external memory. In receiving mode, it converts the resolution of received binary image for compatibility with conventional facsimile. In copy mode, a line of A3 paper with 400 dpi is processed with in 2.5 ms. The prototype of image processor was implemented usig Laser Programmable Gate Array (LPGA) with 0.8.mu.m technology.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2002.10a
• /
• pp.654-658
• /
• 2002

The purpose of this paper is to establish an effective featured based inspection planning system for OMM(On-Machine Measurement) process. In this system, an effective inspection process planning is accomplished by determining the number of measuring points, their locations and probing paths using fuzzy logic, Hammersley method and TSP problem. Also, an effective collision-free algorithm Is proposed based on the EZ-map analysis. All the inspection planning processes are performed based on the defined inspection features those are derived from the CAD database. Proposed inspection planning method is simulated for the given sample wrokpieces, and the results are analyzed. The results show that the proposed method can be successfully implemented in real OMM process.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2014.07a
• /
• pp.419-422
• /
• 2014

본 논문에서는 환자와 검사자에게 초음파 영상의 객관화된 정보를 정확하게 제공하기 위해 간과 신장의 초음파 영상에 SOM 기법을 적용하여 지방간 농도 수치를 분류하는 방법을 제시한다. 제안된 방법은 간, 신장 영역을 촬영한 초음파 영상에서 촬영정보나 눈금자 등과 같이 필요 없는 부분을 잡음으로 간주하여 제거한 Region Of Interest(ROI) 영상을 추출하고, 추출된 ROI 영상에서 명암대비를 강조하기 위해 Fuzzy Stretching 기법을 적용한다. Stretching된 영상에 Enhanced Average Binary와 Labeling 기법으로 적용하여 얻은 Contour 정보를 분석하여 잡음을 제거한 후, 지방간의 측정 영역을 추출한다. 추출된 간과 신장의 측정 영역에 SOM 기법을 적용하여 명암도 값을 분류한 후, 간과 신장의 실질 영역의 대표 명암도를 각각 추출하여 비교 분석한다. 제안된 방법을 초음파 영상에 적용한 결과, 효율적이고 객관적으로 간의 지방도를 분류할 수 있는 가능성을 확인하였다.

• Journal of Power System Engineering
• /
• v.15 no.5
• /
• pp.83-90
• /
• 2011

In general, 20-high Sendzimir mills(ZRM) use small diameter work rolls to provide massive rolling force. Because of small diameter of work rolls, steel strip has a complex shape mixed with quarter, edge and center waves. Especially when the shape of the strip is controlled automatically, the actuator saturation occurs. These problems affect the productivity and quality of products. In this paper, the problems in automatic shape control of ZRM were analyzed. In order to evaluate the problems for the automatic shape control in ZRM, recognition performance was analyzed by comparing the measured shape and the recognized shape. The actuator positions by the shape recognition and the manual operation were compared. From the analysis results, the necessity of the improvement of recognition performance in ZRM is suggested.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2003.11a
• /
• pp.201-206
• /
• 2003

In clinical practice, CT Angiography is a powerful technique for the visualziation of blood flow in arterial vessels throughout the body. However CT Angiography images of blood vessels anywhere in the body may be fuzzy if the patient moves during the exam. In this paper, we propose a novel technique for removing global motion artifacts in the 3D space. The proposed methods are based on the two key ideas as follows. First, the method involves the extraction of a set of feature points by using a 3D edge detection technique based on image gradient of the mask volume where enhanced vessels cannot be expected to appear, Second, the corresponding set of feature points in the contrast volume are determined by correlation-based registration. The proposed method has been successfully applied to pre- and post-contrast CTA brain dataset. Since the registration for motion correction estimates correlation between feature points extracted from skull area in mask and contrast volume, it offers an accelerated technique to accurately visualize blood vessels of the brain.

• Smart Structures and Systems
• /
• v.32 no.2
• /
• pp.111-121
• /
• 2023

This study proposes an automated assembly performance evaluation method for prefabricated steel structures (PSSs) using machine learning methods. Assembly component images were segmented using a modified version of the receptive field pyramid. By factorizing channel modulation and the receptive field exploration layers of the convolution pyramid, highly accurate segmentation results were obtained. After completing segmentation, the positions of the bolt holes were calculated using various image processing techniques, such as fuzzy-based edge detection, Hough's line detection, and image perspective transformation. By calculating the distance ratio between bolt holes, the assembly performance of the PSS was estimated using the k-nearest neighbors (kNN) algorithm. The effectiveness of the proposed framework was validated using a 3D PSS printing model and a field test. The results indicated that this approach could recognize assembly components with an intersection over union (IoU) of 95% and evaluate assembly performance with an error of less than 5%.

• The Bulletin of The Korean Astronomical Society
• /
• v.45 no.1
• /
• pp.44.1-44.1
• /
• 2020

Hα jets of cool chromospheric plasma are protruding into the solar corona 10-100 Mm above the photosphere. The driving mechanisms of Hα jets have been widely studied for decades. However, the detailed process is still elusive. We observed shock signatures moving along a dark jet using 1.6 meter Goode Solar Telescope at Big Bear Solar Observatory. The first shock front of the jet shows sharp --- when it moves upward, while fuzzy and granulated when it moves downward. The jet itself extends upward when the second shock front of the jet reaches the top of the jet. We find abrupt EUV brightenings when the second shock front collides with the edge of the jet. The third front and the fouth front quasi-periodically. These phenomena might be the signs of the rebound shock waves triggered by p-mode wave leakages at the bottom of the jets. Our observation suggests that the jet can be triggered by the rebound shock waves generated by the p-mode waves leaked at the bottom of the jets.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2008.05a
• /
• pp.135-138
• /
• 2008

본 논문은 의료 영상에 대한 효과적인 분류와 검색을 위한 알고리즘을 제안한다. 영상 분류와 검색을 위해서 MPEG-7 표준 기술자인 색 구조 기술자와 경계선 히스토그램 기술자를 사용해 영상들에 대한 특징 값을 추출한다. 이렇게 구해진 특징 값들을 의료 영상의 분류와 검색에 적용해 본 결과 비교적 낮은 성능을 보여줌을 확인하고 앞서 구해진 특징 값들을 교사 학습 방법인 SVM(Support Vector Machine)과 비교사 학습 방법인 FCM(Fuzzy C-means Clustering)에 적용시켰다. 기존 연구에서는 SVM과 FCM의 통합으로 의료 영상에 대한 분류와 검색을 시행하였지만 본 논문에서 실험한 결과 SVM과 MPEG-7 시각 기술자 중에 하나인 EHD(Edge Histogram Descriptor)를 가중치 선형 결합하여 실험한 결과가 더 정확한 분류와 높은 검색 성능을 나타냄을 확인하였다.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.7
• /
• pp.1380-1386
• /
• 2007

This paper proposed an automatic recognition system of shipping container identifiers using fuzzy-based noise removal method and ART2-based self-organizing supervised learning algorithm. Generally, identifiers of a shipping container have a feature that the color of characters is blacker white. Considering such a feature, in a container image, all areas excepting areas with black or white colors are regarded as noises, and areas of identifiers and noises are discriminated by using a fuzzy-based noise detection method. Areas of identifiers are extracted by applying the edge detection by Sobel masking operation and the vertical and horizontal block extraction in turn to the noise-removed image. Extracted areas are binarized by using the iteration binarization algorithm, and individual identifiers are extracted by applying 8-directional contour tacking method. This paper proposed an ART2-based self-organizing supervised learning algorithm for the identifier recognition, which improves the performance of learning by applying generalized delta learning and Delta-bar-Delta algorithm. Experiments using real images of shipping containers showed that the proposed identifier extraction method and the ART2-based self-organizing supervised learning algorithm are more improved compared with the methods previously proposed.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.6
• /
• pp.621-628
• /
• 2015

This paper describes an algorithm for detecting vehicles detection in real time. The proposed algorithm has the technique based on computer vision and image processing. In real, complex environment such as one with road traffic, many algorithms have great difficulty such as low detection rate and increasing computational time due to complex backgrounds and rapid changes. To overcome this problem in this paper, the proposed algorithm consists of the following methods. First, to effectively separate the candidate regions, we use vertical and horizontal edge information, and shadow values from input image sequences. Second, we extracts features by using HOG from the selected candidate regions. Finally, this paper uses the OS fuzzy-ELM based on SLFN to classify the extracted features. The experimental results show that the proposed method perform well for detecting vehicles and improves the accuracy and the computational time of detecting.