• Current Optics and Photonics
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• 제2권5호
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• pp.422-430
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• 2018

Rolling shutter operation of CMOS cameras can be utilized in optical camera communications in order to transmit data from an LED to mobile devices such as smart-phones. From temporally modulated light, a spatial flicker pattern is obtained in the captured image, and this is used for signal recovery. Due to the degradation of rolling shutter images caused by light smear, motion blur, and focus blur, the conventional decoding schemes for rolling shutter cameras based on the pattern width for 'OFF' and 'ON' cannot guarantee robust communications performance for practical uses. Aside from conventional techniques, such as polynomial fitting, histogram equalization can be used for blurry light mitigation, but it requires additional computation abilities resulting in burdens on mobile devices. This paper proposes a transition-based decoding scheme for rolling shutter cameras in order to offer simple and robust data decoding in the presence of image degradation. Based on the designed synchronization pulse and modulated data symbols according to the LED dimming level, the decoding process is conducted by observing the transition patterns of two sequential symbol pulses. For this, the extended symbol pulse caused by consecutive symbol pulses with the same level determines whether the second pulse should be included for the next bit decoding or not. The proposed method simply identifies the transition patterns of sequential symbol pulses other than the pattern width of 'OFF' and 'ON' for data decoding, and thus, it is simpler and more accurate. Experimental results ensured that the transition-based decoding scheme is robust even in the presence of blurry lights in the captured image at various dimming levels

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권3호
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• pp.172-179
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• 2015

Because of the development of computers and high-technology applications, all devices that we use have become more intelligent. In recent years, security and surveillance systems have become more complicated as well. Before new technologies included video surveillance systems, security cameras were used only for recording events as they occurred, and a human had to analyze the recorded data. Nowadays, computers are used for video analytics, and video surveillance systems have become more autonomous and automated. The types of security cameras have also changed, and the market offers different kinds of cameras with integrated software. Even though there is a variety of hardware, their capabilities leave a lot to be desired. Therefore, this drawback is trying to compensate by dint of computer program solutions. Image processing is a very important part of video surveillance and security systems. Capturing an image exactly as it appears in the real world is difficult if not impossible. There is always noise to deal with. This is caused by the graininess of the emulsion, low resolution of the camera sensors, motion blur caused by movements and drag, focus problems, depth-of-field issues, or the imperfect nature of the camera lens. This paper reviews image processing, pattern recognition, and image digitization techniques, which will be useful in security services, to analyze bio-images, for image restoration, and for object classification.

• 한국해양공학회지
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• 제34권6호
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• pp.442-453
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• 2020

Underwater color images suffer from low visibility and color cast effects caused by light attenuation by water and floating particles. This study applied single image enhancement techniques to enhance the quality of underwater images and compared their performance with real underwater images taken in Korean waters. Dark channel prior (DCP), gradient transform, image fusion, and generative adversarial networks (GAN), such as cycleGAN and underwater GAN (UGAN), were considered for single image enhancement. Their performance was evaluated in terms of underwater image quality measure, underwater color image quality evaluation, gray-world assumption, and blur metric. The DCP saturated the underwater images to a specific greenish or bluish color tone and reduced the brightness of the background signal. The gradient transform method with two transmission maps were sensitive to the light source and highlighted the region exposed to light. Although image fusion enabled reasonable color correction, the object details were lost due to the last fusion step. CycleGAN corrected overall color tone relatively well but generated artifacts in the background. UGAN showed good visual quality and obtained the highest scores against all figures of merit (FOMs) by compensating for the colors and visibility compared to the other single enhancement methods.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1315-1318
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• 2003

In this paper, a neural network based approach using a self-organizing feature map is proposed for the segmentation of X ray images. A number of algorithms based on such approaches as histogram analysis, region growing, edge detection and pixel classification have been proposed for segmentation of general images. However, few approaches have been applied to X ray image segmentation because of blur of the X ray image and vagueness of its edge, which are inherent properties of X ray images. To this end, we develop a new model based on the neural network to detect objects in a given X ray image. The new model utilizes Mumford-Shah functional incorporating with a modified adaptive SOFM. Although Mumford-Shah model is an active contour model not based on the gradient of the image for finding edges in image, it has some limitation to accurately represent object images. To avoid this criticism, we utilize an adaptive self organizing feature map developed earlier by the authors.[1] It's learning rule is derived from Mumford-Shah energy function and the boundary of blurred and vague X ray image. The evolution of the neural network is shown to well segment and represent. To demonstrate the performance of the proposed method, segmentation of an industrial part is solved and the experimental results are discussed in detail.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권3호
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• pp.1043-1064
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• 2020

A kind of Subjective Imaging Effect Assessment (SIEA) method and its applications on intelligent imaging terminal design in engineering site are presented. First, some visual assessment indices are used to characterize the imaging effect: the image brightness, the image brightness uniformity, the color image contrast, the image edge blur, the image color difference, the image saturation, the image noise, and the integrated imaging effect index. A linear weighted function is employed to carry out the SIEA computation and the Analytic Hierarchy Process (AHP) technique is used to estimate its weights. Second, a SIEA software is developed. It can play images after the settings of assessment index or assessment reaction time, etc. Third, two cases are used to illustrate the application effects of proposed method: the image enhancement system design for surveillance camera and the imaging environment perception system design for intelligent lighting terminal. A Prior Sequential Stimulus (PSS) experiment is proposed to improve the evaluation stability of SIEA method. Many experiment results have shown the proposed method can realize a stable system design or parameters setting for the intelligent imaging terminal in engineering site.

• 방송공학회논문지
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• 제21권2호
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• pp.272-275
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• 2016

본 논문은 위성 영상을 위한 안개 제거 및 표면반사율 기반의 특징점 검출 방법을 제안한다. 기존의 안개 제거를 위한 DCP 방법은 패치 기반의 처리 방식으로 인해 전달맵 생성 과정에서 블록현상이 발생하게 되고, 이는 영상을 흐리게 하는 원인이 된다. 따라서 제안한 은닉마코프 기반의 방법은 영상의 블록 현상을 제거하고 선명도를 향상한다. 또한 표면반사율 기반의 견고한 특징점 추출을 통해서 영상 정합의 정확성을 향상하였다. 실험을 통해 제안한 방법이 기존 방법에 비해 안개 제거의 성능에서 우수함을 확인하였으며 이를 통해 특징 검출 및 위성 영상 정합에 적합함을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권8호
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• pp.4005-4025
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• 2019

Copy-move forgery (CMF) in digital images is a detrimental tampering of artefacts that requires precise detection and analysis. CMF is performed by copying and pasting a part of an image into other portions of it. Despite several efforts to detect CMF, accurate identification of noise, blur and rotated region-mediated forged image areas is still difficult. A novel algorithm is developed on the basis of quaternion polar complex exponential transform (QPCET) to detect CMF and is conducted involving a few steps. Firstly, the suspicious image is divided into overlapping blocks. Secondly, invariant features for each block are extracted using QPCET. Thirdly, the duplicated image blocks are determined using k-dimensional tree (kd-tree) block matching. Lastly, a new technique is introduced to reduce the flat region-mediated false matches. Experiments are performed on numerous images selected from the CoMoFoD database. MATLAB 2017b is used to employ the proposed method. Metrics such as correct and false detection ratios are utilised to evaluate the performance of the proposed CMF detection method. Experimental results demonstrate the precise and efficient CMF detection capacity of the proposed approach even under image distortion including rotation, scaling, additive noise, blurring, brightness, colour reduction and JPEG compression. Furthermore, our method can solve the false match problem and outperform existing ones in terms of precision and false positive rate. The proposed approach may serve as a basis for accurate digital image forensic investigations.

• Journal of the Optical Society of Korea
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• 제1권2호
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• pp.90-93
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• 1997

The shallow depth of focus in conventional light microscopy hinders the observation of the whole image when the object is thicker than the depth of field. Most of the existing techniques measured the object distance, which is not necessarily the actual distance of each pixel in the image. We implemented a means of determining the "best focus" of each pixel and located the height of object points by sectioning at different sample heights. Combining the height information and its gray values together, we obtained an image where the blur from the finite depth of focus is eliminated. Limitations of the technique are discussed together with composed images.ed images.

• 전기전자학회논문지
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• 제3권2호
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• pp.168-177
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• 1999

이 논문은 디지털 영상에 대한 에지를 보존하는 새로운 영상 보간 방법을 제안한다. 일반적인 보간 기법은 선형 연산자를 이용한 저역필터를 사용함으로써 원 영상의 고조파 성분에 대한 정보를 손실하는바 high contrast 에지 부분에서 희뿌옇게 되는 현상과 톱니현상이 일어나 영상 선명도가 떨어지는 경향이 있었다. 본 논문에서는 이러한 단점을 개선한 새로운 보간 기법을 제시한다. 본 논문에서 제시한 보간 알고리즘은 퍼지 연산자를 이용하여 입력 영상 데이터의 성질에 따라 고주파 성분과 저주파 성분을 달리 조절함으로써 원래 영상에 가까운 해상도를 얻을 수 있다.

• Journal of the Optical Society of Korea
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• 제19권5호
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• pp.456-466
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• 2015

We investigated an anti-aliasing (AA) filter for digital camera photography by which the excessively high-frequency components of the image signal are suppressed to avoid the aliasing effect. Our optomechanical AA filter was implemented by applying rapid relative motions to the imaging sensor. By the engineered motion blur of the mechanical dithers, the effective point-spread function (PSF) of the imaging system could be tailored to reject the unwanted high-frequency components of the image. For optimal operations, we developed a spiral filter motion protocol that could produce a Gaussian-like PSF. We experimentally demonstrated that our AA filter provides an improved filtering characteristic with a better compromise of the rejection performance and the signal loss. We also found that the pass band characteristic can be enhanced further by a color-differential acquisition mode. Our filter scheme provides a useful method of digital photography for low-error image measurements as well as for ordinary photographic applications where annoying $moir{\acute{e}}$ patterns must be suppressed efficiently.