• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권10호
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• pp.2514-2526
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• 2013

This paper presents a detection method for least significant bit matching revisited (LSBMR) steganography. Previous research shows that the adjacent pixels of natural images are highly correlated and the value 0 appears most frequently in pixel difference. Considering that the message embedding process of LSBMR steganography has a weighted-smoothing effect on the distribution of pixel difference, the frequency of the occurrence of value 0 in pixel difference changes most significantly whereas other values approximately remain unchanged during message embedding. By analyzing the effect of LSBMR steganography on pixel difference distribution, an equation is deduced to estimate the frequency of difference value 0 using the frequencies of difference values 1 and 2. The sum of the ratio of the estimated value to the actual value as well as the ratio of the frequency of difference value 1 to difference value 0 is used as the steganalytic detector. Experimental results show that the proposed method can effectively detect LSBMR steganography and can outperform previous proposed methods.

• 한국정보전자통신기술학회논문지
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• 제9권6호
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• pp.573-577
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• 2016

본 논문에서는 영상의 지역성과 인접 픽셀 차분시퀀스를 이용하는 가역 데이터 임베딩 기법을 제안하였다. 자연영상에는 일반적으로 지역성이 존재한다. 영상의 지역성을 이용하여 인접한 픽셀 값을 예측하는 기법을 기존의 기법인 APD(Adjacent Pixel Difference) 기법에 적용하여 임베딩 가능한 데이터 량을 증가 시키고 다양한 레벨로 데이터 임베딩을 가능하게 하는 가역 데이터 임베딩 기법을 제안하였다. 실험결과를 통하여 제안된 기법의 우수성을 확인하였다.

• Journal of Information Processing Systems
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• 제15권2호
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• pp.261-270
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• 2019

In order to protect secret digital documents against vulnerabilities while communicating, steganography algorithms are applied. It protects a digital file from unauthorized access by hiding the entire content. Pixel-value-difference being a method from spatial domain steganography utilizes the difference gap between neighbor pixels to fulfill the same. The proposed approach is a block-wise embedding process where blocks of variable size are chosen from the cover image, therefore, a stream of secret digital contents is hidden. Least significant bit (LSB) substitution method is applied as an adaptive mechanism and optimal pixel adjustment process (OPAP) is used to minimize the error rate. The proposed application succeeds to maintain good hiding capacity and better signal-to-noise ratio when compared against other existing methods. Any means of digital communication specially e-Governance applications could be highly benefited from this approach.

• Journal of Information Technology Applications and Management
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• 제10권3호
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• pp.45-54
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• 2003

Security system with web camera remarkably has been developed at an Internet era. Using transmitted images from remote camera, the system can recognize current situation and take a proper action through web. Existing motion detection methods use simply difference image, background image techniques or block matching algorithm which establish initial block by set search area and find similar block. But these methods are difficult to detect exact motion because of useless noise. In this paper, the proposed method is updating changed background image as much as $N{\times}M$pixel mask as time goes on after get a difference between imput image and first background image. And checking image pixel can efficiently detect motion by computing fixed distance pixel instead of operate all pixel.

• 대한원격탐사학회지
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• 제31권1호
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• pp.21-28
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• 2015

The essential idea of de-noising is referring to neighboring pixels of a center pixel to be updated. Conventional adaptive de-noising filters use local statistics, i.e., mean and variance, of neighboring pixels including the center pixel. The drawback of adaptive de-noising filters is that their performance becomes low when edges are contained in neighboring pixels, while anisotropic diffusion de-noising filters remove adaptively noises and preserve edges considering intensity difference between neighboring pixel and the center pixel. The anisotropic diffusion de-noising filters, however, use only intensity difference between neighboring pixels and the center pixel, i.e., local statistics of neighboring pixels and the center pixel are not considered. We propose a new connectivity function of two adjacent pixels using statistics of neighboring pixels and apply connectivity function to diffusion coefficient. Experimental results using an aerial image corrupted by uniform and Gaussian noises showed that the proposed algorithm removed more efficiently noises than conventional diffusion filter and median filter.

• Current Optics and Photonics
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• 제4권5호
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• pp.428-433
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• 2020

Recently, the on-chip autofocus (AF) function has become essential to the CMOS image sensor. An auto-focus usually operates using phase detection of the photocurrent difference from a pair of AF pixels that have focused or defocused. However, the phase-detection method requires a pair of AF pixels for comparison of readout. Therefore, the pixel variation may reduce AF performance. In this paper, we propose a color-selective AF pixel with a plasmonic nanostructure in a 0.9 μ㎡ pixel. The suggested AF pixel requires one pixel for AF function. The plasmonic nanostructure uses metal-insulator-metal (MIM) stack arrays instead of a color filter (CF). The color filters are formed at the subwavelength, and they transmit the specific wavelength of light according to the stack period and incident angles. For the optical analysis of the pixel, a finite-difference time-domain (FDTD) simulation was conducted. The analysis showed that the MIM stack arrays in the pixels perform as an AF pixel. As the primary metric of AF performance, the resulting AF contrasts are 1.8 for the red pixels, 1.6 for green, and 1.5 blue. Based on the simulation results, we confirmed the autofocusing performance of the MIM stack arrays.

• 문화기술의 융합
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• 제6권1호
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• pp.449-454
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• 2020

본 논문에서는 하나의 필드만을 사용하여 비월 주사 영상을 순차 주사 영상으로 변환하는 개선된 디인터레이싱 방법을 제안한다. 먼저, 구하고자 하는 화소의 위와 아래 각각 5개 화소를 이용하여 세분화된 화소 사이의 값들을 Newton의 전향차분과 후향차분을 이용하여 구한다. 이렇게 얻어진 화소 사이의 값과 5개의 알려진 화소값들을 이용하여 구하고자하는 화소를 중심으로 위와 아래화소의 방향을 세분화하여 각각의 상관관계를 구한다. 구하고자 하는 화소에서의 에지의 방향성은 위와 아래 상관관계가 가장 최소가 되는 방향으로 예측한다. 구하고자 하는 화소값 결정은 예측된 방향에 따라 위와 아래 화소값의 평균값으로 결정한다. 모의실험 결과 기존의 제시된 여러 디인터레이싱 방법에 비해 엣지에서의 주관적 화질이 개선되었으며 또한 객관적 화질에 있어서 정량적으로 PSNR 계산결과 0.2~0.3dB정도의 화질개선이 이루어졌다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제27권5호
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• pp.543-550
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• 2000

블럭 정합 알고리즘의 VLSI 구현시 복잡도를 줄이고, 수행 속도를 높이기 위하여 새로운 정합 기준인 적응적 비트 축소 MAD(adaptive bit-reduced mean absolute difference:ABRMAD)를 제안한다. ABRMAD는 기존의 MAD에서 화소의 모든 비트를 비교하는 대신, 화소를 구성하는 중요한 비트만을 고려하여 축소된 화소 값을 비교하여 움직임 벡터를 찾는다. 실험을 통하여, 제안한 정합 기준은 기존의 MAD 정합 기준에 비하여 낮은 하드웨어 복잡도를 가지면서 MSE(mean square error) 측면에서 유사한 성능을 가짐을 보인다. 또한 기존의 비트 수 축소형 정합 기준인 DPC(difference pixel counting), BBME(binary-matching with edge-map), 그리고 BPM(bit-plane matching)과 비교하여 같은 수의 비트를 사용하였을 경우 좋은 MSE 성능을 가짐을 보인다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권11호
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• pp.5481-5495
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• 2018

Single pixel imaging technology has developed for years, however the video acquisition on the single pixel camera is not a well-studied problem in computer vision. This work proposes a new scheme for single pixel camera to acquire video data and a new regularization for robust signal recovery algorithm. The method establishes a single pixel video compressive sensing scheme to reconstruct the video clips in spatial domain by recovering the difference of the consecutive frames. Different from traditional data acquisition method works in transform domain, the proposed scheme reconstructs the video frames directly in spatial domain. At the same time, a new regularization called spatial cluster is introduced to improve the performance of signal reconstruction. The regularization derives from the observation that the nonzero coefficients often tend to be clustered in the difference of the consecutive video frames. We implement an experiment platform to illustrate the effectiveness of the proposed algorithm. Numerous experiments show the well performance of video acquisition and frame reconstruction on single pixel camera.

• 센서학회지
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• 제29권2호
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• pp.123-127
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• 2020

In this paper, the estimation of the disparity for depth extraction in monochrome complementary metal-oxide-semiconductor (CMOS) image sensors with offset pixel apertures is presented. To obtain the depth information, the disparity information between two different channel data of the offset pixel apertures is required. The disparity is caused by the difference in the response angle between the left- and right-offset pixel aperture images. A depth map is implemented by the generated disparity. Therefore, the disparity is the most important factor for realizing 3D images from the designed CMOS image sensor with offset pixel apertures. The disparity is influenced by the pixel height and offset value of the offset pixel aperture. To confirm this correlation, the offset value is set to maximum within the pixel area, and the disparity values corresponding to the difference in the heights are calculated and compared. The disparity is derived using the camera-lens formula. Two monochrome CMOS image sensors with offset pixel apertures are used in the disparity estimation.