• 대한공간정보학회지
• /
• 제4권1호
• /
• pp.67-73
• /
• 1996

본 논문은 수치영상으로부터 컴퓨터비전(Computer Vision), 수치사진측량학(야?w미 Photogrammmetry)분야에서 특이점(Distinct Point)이나 Linear Feature를 추출하기 위해서 가장 많이 이용되고 있는 $F\"{o}rstner$ interest operator의 Scale space에 관한 연구이다. 수치사진측량분야에서 사용되고 있는 수치영상자료의 크기를 고려할 때, Scale space 즉 Image pyramid는 수치영상 처리속도를 향상시킬 수 있는 방법으로 서서히 주목받고 있다. 본 연구에서는 Gaussian에 의해서 구축된 Scale space에서 $F\"{o}rstner$ interest operator의 거동을 고찰하였고, 실제 수치사진 영상에 적용하여 실제적용 여부를 검증하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제14권10호
• /
• pp.4060-4079
• /
• 2020

Blur is an important type of image distortion. How to evaluate the quality of blurred image accurately and efficiently is a research hotspot in the field of image processing in recent years. Inspired by the multi-scale perceptual characteristics of the human visual system (HVS), this paper presents a no-reference image blur/sharpness assessment method based on multi-scale local features in the spatial domain. First, considering various content has different sensitivity to blur distortion, the image is divided into smooth, edge, and texture regions in blocks. Then, the Gaussian scale space of the image is constructed, and the categorized contrast features between the original image and the Gaussian scale space images are calculated to express the blur degree of different image contents. To simulate the impact of viewing distance on blur distortion, the distribution characteristics of local maximum gradient of multi-resolution images were also calculated in the spatial domain. Finally, the image blur assessment model is obtained by fusing all features and learning the mapping from features to quality scores by support vector regression (SVR). Performance of the proposed method is evaluated on four synthetically blurred databases and one real blurred database. The experimental results demonstrate that our method can produce quality scores more consistent with subjective evaluations than other methods, especially for real burred images.

• 대한의용생체공학회:의공학회지
• /
• 제36권1호
• /
• pp.22-30
• /
• 2015

Melanoma is originated from the melanocyte producing the melanin which determines the complexion, and it has the highest mortality among skin cancers. Acral lentiginous melanoma(ALM) arises from extremities such as hands, feet or fingernails. Since the appearance of ALM is different from melanoma on the body, conventional auto diagnosis systems for melanoma is inappropriate to detect ALM. Therefore, ALM is typically difficult to distinguish from general nevus, resulting in delayed diagnosis and bad prognosis. In this paper, we firstly introduce a determination method for ALM by dermatologists and propose a method to rotate dermoscopic images automatically as a pre-processing for facilitating the easy determination of ALM and to select the optimal value of the Gaussian differentiation filter parameter which is significant for precise pattern extraction using the scale space analysis. From experimental results, it is shown that there exists the consistency between empirical values of the Gaussian differential filter parameter and optimal values derived from the scale space analysis to distinguish nevus and ALM.

• 전기학회논문지P
• /
• 제62권2호
• /
• pp.90-94
• /
• 2013

In this paper, we propose a new algorithm to improve the contrast ratio, to preserve information of bright regions and to maintain the color of backlight image that appears with a great relative contrast. Backlight images of the natural environment have characteristics for difference of local brightness; the overall image contrast improvement is not easy. To improve the contrast of the backlight images, MSR (Multi-Scale Retinex) algorithm using the existing multi-scale Gaussian filter is applied. However, existing multi-scale Gaussian filter involves color distortion and information loss of bright regions due to excessive contrast enhancement and noise because of the brightness improvement of dark regions. Moreover, it also increases computational complexity due to the use of multi-scale Gaussian filter. In order to solve these problems, a linear MSR is performed that reduces the amount of computation from the HSV color space preventing the color distortion and information loss due to excessive contrast enhancement. It can also remove the noise of the dark regions which is occurred due to the improved contrast through edge preserving filter. Through experimental evaluation of the average color difference comparison of CIELAB color space and the visual assessment, we have confirmed excellent performance of the proposed algorithm compared to conventional MSR algorithm.

• 제어로봇시스템학회논문지
• /
• 제6권12호
• /
• pp.1113-1119
• /
• 2000

To operate a process plant safely and economically, process monitoring is very important. Process monitoring is the task to identify the state of the system from sensor data. Process monitoring includes data acquisition, regulatory control, data reconciliation, fault detection, etc. This research focuses on the data recon-ciliation using scale-space filtering and fault detection using functional-link associative neural networks. Scale-space filtering is a multi-resolution signal analysis method. Scale-space filtering can extract highest frequency factors(noise) effectively. But scale-space filtering has too large calculation costs and end effect problems. This research reduces the calculation cost of scale-space filtering by applying the minimum limit to the gaussian kernel. And the end-effect that occurs at the end of the signal of the scale-space filtering is overcome by using extrapolation related with the clustering change detection method. Nonlinear principal component analysis methods using neural network have been reviewed and the separately expanded functional-link associative neural network is proposed for chemical process monitoring. The separately expanded functional-link associative neural network has better learning capabilities, generalization abilities and short learning time than the exiting-neural networks. Separately expanded functional-link associative neural network can express a statistical model similar to real process by expanding the input data separately. Combining the proposed methods-modified scale-space filtering and fault detection method using the separately expanded functional-link associative neural network-a process monitoring system is proposed in this research. the usefulness of the proposed method is proven by its application a boiler water supply unit.

• Journal of Astronomy and Space Sciences
• /
• 제38권3호
• /
• pp.165-173
• /
• 2021

Apophis is a near-Earth object with a diameter of approximately 340 m, which will come closer to the Earth than a geostationary orbit in 2029, offering a unique opportunity for characterizing the object during the upcoming encounter. Therefore, Korea Astronomy and Space Science Institute has a plan to propose a space mission to explore the Apophis asteroid using scientific instruments such as a laser altimeter. In this study, we evaluate the performance metrics of a laser altimeter using a pseudorandom noise modulation technique for the Apophis mission, in terms of detection probability and ranging accuracy. The closed-form expression of detection probability is provided using the cross correlation between the received pulse trains and pseudo-random binary sequence. And the new ranging accuracy model using Gaussian error propagation is also derived by considering the sampling rate. The operation range is significantly limited by thermal noise rather than background noise, owing to not only the low power laser but also the avalanche photodiode in the analog mode operation. However, it is demonstrated from the numerical simulation that the laser altimeter can achieve the ranging performance required for a proximity operation mode, which employs commercially available components onboard CubeSat-scale satellites for optical communications.

• 대한전자공학회논문지SP
• /
• 제49권4호
• /
• pp.85-94
• /
• 2012

차선 마킹 검출은 지능형 운송 시스템(ITS, intelligent transportation systems), 운전자 보조 시스템(DAS, driver assistant systems) 등에 필수적인 요소이다. 이 논문에서는 스케일 공간 기법을 이용하여 기존의 기법들에 비해 견고한 차선 마킹 검출기법을 제안한다. 차선 마킹 검출에 많이 사용되고 있는 지역 통계 기반 가변적 문턱처리 기법은 밝기 특성이 두드러진 객체의 검출에 유리하므로 차선 마킹 검출에 효과적일 수 있다. 그러나 통계적 특징만으로는 무관한 영역도 함께 검출되므로, 이 논문에서는 가변적 문턱처리 결과와 함께 수평 1D LoG 필터링 스케일 공간을 합성하여 차선 마킹 후보 영역을 축소하는 기법을 제안한다. 실제 영상에 대해 가변적 문턱처리뿐만 아니라 차선 마킹 검출을 위한 또 다른 대표적인 기법인 하프 변환을 사용하는 기법과도 비교한 결과, 뚜렷한 차선 마킹 후보 영역 축소를 확인할 수 있었다.

• Wind and Structures
• /
• 제26권1호
• /
• pp.11-24
• /
• 2018

Full-scale measurements of wind action on the open roof structure of the WuXi grand theater, which is composed of eight large-span free-form leaf-shaped space trusses with the largest span of 76.79 m, were conducted during the passage of Typhoons HaiKui and SuLi. The wind pressure field data were continuously and simultaneously monitored using a wind pressure monitoring system installed on the roof structure during the typhoons. A detailed analysis of the field data was performed to investigate the characteristics of the fluctuating wind pressure on the open roof, such as the wind pressure spectrum, spatial correlation coefficients, peak wind pressures and non-Gaussian wind pressure characteristics, under typhoon conditions. Three classical methods were used to calculate the peak factors of the wind pressure on the open roof, and the suggested design method and peak factors were given. The non-Gaussianity of the wind pressure was discussed in terms of the third and fourth statistical moments of the measured wind pressure, and the corresponding indication of the non-Gaussianity on the open roof was proposed. The result shows that there were large pulses in the time-histories of the measured wind pressure on Roof A2 in the field. The spatial correlation of the wind pressures on roof A2 between the upper surface and lower surface is very weak. When the skewness is larger than 0.3 and the kurtosis is larger than 3.7, the wind pressure time series on roof A2 can be taken as a non-Gaussian distribution, and the other series can be taken as a Gaussian distribution.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제11권3호
• /
• pp.1477-1491
• /
• 2017

Inspired by the multi-scale nature of hippocampal place cells, a biologically inspired model based on a multi-scale spatial representation for goal-directed navigation is proposed in order to achieve robotic spatial cognition and autonomous navigation. First, a map of the place cells is constructed in different scales, which is used for encoding the spatial environment. Then, the firing rate of the place cells in each layer is calculated by the Gaussian function as the input of the Q-learning process. The robot decides on its next direction for movement through several candidate actions according to the rules of action selection. After several training trials, the robot can accumulate experiential knowledge and thus learn an appropriate navigation policy to find its goal. The results in simulation show that, in contrast to the other two methods(G-Q, S-Q), the multi-scale model presented in this paper is not only in line with the multi-scale nature of place cells, but also has a faster learning potential to find the optimized path to the goal. Additionally, this method also has a good ability to complete the goal-directed navigation task in large space and in the environments with obstacles.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2006년도 추계학술발표대회
• /
• pp.89-92
• /
• 2006

본 논문은 SIFT(Scale Invariant Feature Transform)알고리즘의 실시간처리 응용프로그램 작성기법을 기술하고 있는데, 단일 프로세서에서 병렬처리 기능을 지원하도록 설계된 SSE 명령어 집합을 사용하여 가우시안 convolution을 구현하고 있다. SIFT알고리즘의 Scale-space를 생성하는 과정에 수행되는 가우시안 Convolution은 연산시간이 과도하게 요구된다.[1] 2D의 가우시안 필터가 영상을 구성하는 모든 셀과 1:1로 연산을 수행하므로 이 연산의 소요시간은 영상의 가로, 세로 길이 그리고 필터의 크기에 비례하여 결정된다. 이 논문에서 제안하는 방법은 연산을 위해 CPU 내부로 한번 읽어 들인 픽셀자료에 대해 가능한 모든 연산을 SSE 명령어 집합을 사용하여 수행함으로써 병렬 연산에 의한 연산시간 절감과 메모리 접근 최소화를 통한 입출력시간 절감을 통해 전체 연산시간을 단축 하였다.