• 전기학회논문지
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• 제61권12호
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• pp.1926-1931
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• 2012

We investigated a novel fast non-uniform illumination correction method for bi-level images. The proposed method divides a bi-level image into sub-images and roughly estimates block-wise illumination by low pass filtered maximum values of sub-images. After that, we apply bilinear interpolation using the block-wise illumination to estimate non-uniform illumination, and compensate for the effect of non-uniform illumination using the estimated illumination. Since the proposed method is not based on computation intensive iterative optimization, the proposed method can be used effectively for applications that require fast correction of non-uniform illumination. In simulations, the proposed method showed more than 20 times faster speed than existing entropy minimization method. Moreover, in simulations and experiments, the restored images by the proposed method were more close to true images than images restored by conventional method.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.224-229
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• 2009

Digital image recognition has been used for steel bridge surface assessment since late 1990s. However, the non-uniform illumination problems such as shades, shadows, and highlights are still challenges in image processing to date. Therefore, this paper develops a new approach to tackle the non-uniform illumination problem for rust image adjustment. The inhomogeneous illumination problem is divided into shades/shadows and highlights in this paper. The proposed BEMD-morphology approach (BMA) utilizes the bidimensional empirical mode decomposition to mitigate the shade/shadow effect, and the morphological processing to detect and replace the highlight area. Finally, the rust image processed with the BMA will be segmented by the K-Means algorithm, one of the most popular and effective methods, to show the effectiveness of illumination adjustment.

• 방송공학회논문지
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• 제22권2호
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• pp.207-213
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• 2017

다수의 조명을 이용한 멀티스펙트럴 이미징을 정확히 수행하기 위해서는 영상 내 조명의 세기가 균일해야 한다. 멀티스펙트럴 이미징이 아니더라도 정확한 색 정보가 필요한 영상 획득에서는 조명이 정확해야 하고, 정확한 조명 특성을 위해 평면 광원을 사용하거나 조명 캘리브레이션을 수행한다. 본 논문에서는 조명의 세기가 균일하지 않은 영상을 조명의 세기가 균일하도록 색상을 보정하는 방법을 제안한다. 우선 비균일 조명에서 얻은 두 영상으로 멀티스펙트럴 이미징을 수행하여 반사 스펙트럼을 획득하고 획득한 반사 스펙트럼을 형광등이나 태양광과 같은 평면광에서 획득한 영상의 조명 특성으로 재조명한다. 재조명으로 얻은 영상과 평면광 영상의 조도 분포의 차이를 이용해서 비균일 조명 영상을 균일한 영상에서 획득한 영상처럼 색상 보정을 수행한다. 실험 결과로 조명의 비균일성이 균일하게 보정되었는지 확인하고, 이 결과를 통해 영상의 색 정보를 취득하는 데 조명의 제약사항을 줄일 수 있을 것으로 기대된다.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2011년도 춘계학술발표대회 논문집
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• pp.269-274
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• 2011

A solar cell is primary parts to produce electrical energy from the Sun. And, we can utilize those solar cells as a power generation system in home, factory, and so on. In order to make proper power, the solar cells are configured in series and parallel lay down. In condition of uniform illumination, the solar array will produce an enough power by photovoltaic effects from the solar cells. In case of non-uniform illumination on the solar cells, the power will be dramatically decreased compared to design. Fortunately, there were so many research outputs regarding the illumination effects on solar array. In this work, we tried to find out the non-uniform effects on unit CPV solar cell, because there were no research outputs for unit CPV solar cell considering illumination. The CPV solar cell was used in CPV system to make a power by the Sun. We chosen the triple junction solar cell of GaAsInP2Ge for simulation, which has a 30 % of conversion efficiency. By simulation, we obtained the output performance of CPV solar cells in condition of various illumination by using Hamming Window function. Its performance was degraded by 10 % to 50 % depending illumination conditions.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.449-456
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• 2009

Image processing has been applied to steel bridge defect recognition since 1990s. Compare to human visual inspection, image processing provides a more objective and accurate way of assessment. Since shade and shadow may sometimes occur when taking bridge coating images, non-uniform illumination problems should be considered. By means of color image processing, this paper aims to mitigate the illumination effect for bridge coating assessment. Furthermore, the adaptable ellipse method (AEM) is proposed to recognize mild rust colors. Finally, AEM will be compared to the K-Means algorithm, a popular recognition method, to show its advantage.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.257-262
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• 2009

Image processing has been utilized for assessment of infrastructure surface coating conditions for years. However, there is no robust method to overcome the non-uniform illumination problem to date. Therefore, this paper aims to deal with non-uniform illumination problems for bridge coating assessment and to achieve automated rust intensity recognition. This paper starts with selection of the best color configuration for non-uniformly illuminated rust image segmentation. The adaptive-network-based fuzzy inference system (ANFIS) is adopted as the framework to develop the new model, the box-and-ellipse-based neuro-fuzzy approach (BENFA). Finally, the performance of BENFA is compared to the Fuzzy C-Means (FCM) method, which is often used in image recognition, to show the advantage and robustness of BENFA.

• 정보과학회 논문지
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• 제44권3호
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• pp.295-305
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• 2017

얼굴 외형은 조명의 영향을 크게 받기 때문에 조명 변화는 얼굴 인식 시스템의 성능을 저하시키는 요인 중 하나이다. 본 논문에서는 non-alpha Weberface(non-alpha WF)와 히스토그램 평활화를 결합하여 조명 변화에 강건한 얼굴 표현 방법을 제안한다. 먼저, 입력 얼굴 영상에 대해 명암 대비 조절 파라미터를 적용하지 않은 non-alpha WF를 생성한다. 이후, non-alpha WF의 히스토그램 분포를 전역적으로 균일하게 하고 명암 대비를 향상시키기 위해 히스토그램 평활화를 수행한다. 제안하는 방법을 통해 전처리된 얼굴 영상으로부터 저차원 판별 특징을 추출하기 위해 $(2D)^2PCA$를 적용한다. Extended Yale B 및 CMU PIE 얼굴 데이터베이스에 대해 실험한 결과, 제안하는 방법으로 각각 93.31%와 97.25%의 평균 인식률을 얻었다. 또한, 제안하는 방법은 기존 WF뿐만 아니라 여러 조명 처리 방법들과 비교하여 향상된 인식 성능을 보였다.

• 한국멀티미디어학회논문지
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• 제11권12호
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• pp.1649-1657
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• 2008

In this paper, to overcome the failure of binarization for the characters suffered from low contrast and non-uniform illumination in license plate character recognition system, we improved the binarization method by combining local thresholding with global thresholding and edge detection. Firstly, apply the local thresholding method to locate the characters in the license plate image and then get the threshold value for the character based on edge detector. This method solves the problem of local low contrast and non-uniform illumination. Finally, back-propagation Neural Network is selected as a powerful tool to perform the recognition process. The results of the experiments i1lustrate that the proposed binarization method works well and the selected classifier saves the processing time. Besides, the character recognition system performed better recognition accuracy 95.7%, and the recognition speed is controlled within 0.3 seconds.

• 전기전자학회논문지
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• 제22권4호
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• pp.1188-1194
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• 2018

This paper proposes an image enhancement-based license plate detection algorithm to improve the overall performance of system. Non-uniform illumination conditions have huge impact on overall plate detection system accuracy. In this paper, we propose an algorithm for color image enhancement-based license plate detection for improving accuracy of images degraded by excessively strong and low sunlight. Firstly, the image is enhanced by Multi-Scale Retinex algorithm. Secondly, a plate detection method is employed to take advantage of geometric properties of connected components, which can significantly reduce the undesired plate regions. Finally, intersection over union method is applied for detecting the accurate location of number plate. Experimental results show that the proposed method significantly improves the accuracy of plate detection system.

• 한국정보통신학회논문지
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• 제17권2호
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• pp.423-430
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• 2013

최근 손등이나 손바닥, 손가락의 정맥 혈관 패턴정보를 이용하여 개인을 인증하는 기술은 훼손, 복제 및 위조가 불가능하다는 장점으로 인해 연구가 활발하게 진행 중이다. 정맥영상은 피부층과 내부 골격등에 의한 빛의 산란 및 불균일한 내부 조직 때문에 정맥 영역이 뚜렷하게 나타나지 않아, 영상처리 방법을 통해 정맥 영역을 정확하게 분리하는 것이 어렵다. 특히 한 장의 영상에서도 밝기가 균일하지 않아서 지역 영역 단위로 다른 이진 임계치를 사용함으로 인해 처리시간이 오래 걸리고 혈관의 불연속면이 발생한다는 문제가 있다. 이를 해결하기 위해 본 논문에서는 조명 정규화 기반의 고속 정맥 영역 추출 방법을 제안한다. 본 연구는 기존의 방법에 비해 다음과 같은 장점을 가지고 있다. 첫째, 정맥영상의 불균일한 조명을 제거하기 위해 저역통과필터를 통해 조명 성분을 취득하고 이를 통해 조명성분이 균일한 영상을 얻었다. 둘째, 조명 정규화 영상으로부터 단일 임계치를 통해 얻어진 이진 영상의 처리를 통해 혈관 경로를 추출함으로써, 처리시간을 단축하였다. 실험을 통해 기존 방법들에 비해 혈관 영역 추출 정확도가 상승하고, 처리속도가 단축된 결과를 얻을 수 있었다.