• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.2
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• pp.47-52
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• 2016

The used digital images in the smart device and small displayer has been a downscaled image. In this paper, the detection of the downscaling image forgery is proposed using the feature vector according to the pixel value's gradients. In the proposed algorithm, AR (Autoregressive) coefficients are computed from pixel value's gradients of the image. These coefficients as the feature vectors are used in the learning of a SVM (Support Vector Machine) classification for the downscaling image forgery detector. On the performance of the proposed algorithm, it is excellent at the downscaling 90% image forgery compare to MFR (Median Filter Residual) scheme that had the same 10-Dim. feature vectors and 686-Dim. SPAM (Subtractive Pixel Adjacency Matrix) scheme. In averaging filtering ($3{\times}3$) and median filtering ($3{\times}3$) images, it has a higher detection ratio. Especially, the measured performances of all items in averaging and median filtering ($3{\times}3$), AUC (Area Under Curve) by the sensitivity and 1-specificity is approached to 1. Thus, it is confirmed that the grade evaluation of the proposed algorithm is 'Excellent (A)'.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.7
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• pp.467-472
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• 2009

Seedling growth test is used to assess toxicity of nanoparticles (NPs). This study evaluates toxicity of zinc, zinc oxide NPs on Cucumis sativus using two methods; phytagel and filter paper. From the comparison, phytagel method prevents precipitation of water insoluble NPS. Seeding length was negatively related to the exposed concentration of Zn, ZnO NPs in filter method. The median effective concentrations (EC50) for C. sativus exposed to Zn, ZnO NPs were estimated about 598, 600 mg/L in filter method. Bioaccumulation increased with the exposed concentration of Zn, ZnO NPs in only filter method. The results showed that the filter paper method was much better protocol than phytagel method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.8
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• pp.360-367
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• 2002

In this paper, genetic algorithm based adaptive image enhancement filtering scheme is proposed and Implemented on FPGA board. Conventional filtering methods require a priori noise information for image enhancement. In general, if a priori information of noise is not available, heuristic intuition or time consuming recursive calculations are required for image enhancement. Contrary to the conventional filtering methods, the proposed filter system can find optimal combination of filters as well as their sequent order and parameter values adaptively to unknown noise types using structured genetic algorithms. The proposed image enhancement filter system is mainly composed of two blocks. The first block consists of genetic algorithm part and fitness evaluation part. And the second block consists of four types of filters. The first block (genetic algorithms and fitness evaluation blocks) is implemented on host computer using C code, and the second block is implemented on re-configurabe FPGA board. For gray scale control, smoothing and deblurring, four types of filters(median filter, histogram equalization filter, local enhancement filter, and 2D FIR filter) are implemented on FPGA. For evaluation, three types of noises are used and experimental results show that the Proposed scheme can generate optimal set of filters adaptively without a pioi noise information.

• Journal of Information Processing Systems
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• v.7 no.1
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• pp.103-110
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• 2011

In this paper, an adaptive motion vector smoothing scheme based on weighted vector median filtering is proposed in order to eliminate the motion outliers more effectively for improving the quality of side information in frame-based distributed video coding. We use a simple motion vector outlier reliability measure for each block in a motion compensated interpolated frame and apply weighted vector median filtering only to the blocks with unreliable motion vectors. Simulation results show that the proposed adaptive motion vector smoothing algorithm improves the quality of the side information significantly while maintaining low complexity at the encoder in frame-based distributed video coding.

• Journal of Biomedical Engineering Research
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• v.17 no.4
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• pp.507-514
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• 1996

The automated ECG diagnostic systems in hospital have a low P-wave detection capacity in case of some diseases like conduction block. The purpose of this study is to improve the P-wave detection ca- pacity using wavelet transform. The first procedure is to remove baseline drift by subtracting the median filtered signal from the original signal. The second procedure is to cancel ECG's QRS-T complex from median filtered signal to get P-wave candidate. Before we subtracted the templete from QRS-T complex, we estimated the best matching between templete and QRS-T complex to minimize the error. Then, wavelet transform was applied to confirm P-wave. In particular, haiti wavelet was used to magnify P-wave that consisted of low frequency components and to reject high frequency noise of QRS-T complex cancelled signal. Finally, p-wave was discriminated and confirmed by threshold value. By using this method, We can got the around 95.1% P-wave detection. It was compared with contextual information.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.747-750
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• 2001

The paper presents an algorithm for estimating the variance of additive zero mean Gaussian noise in an image. The algorithm uses the wavelet transform which is a good tool for energy compaction. The algorithm consists of three steps. At first, high frequency components, wavelet coefficients in HH band, are generated from a noisy image by the wavelet transform. In a second step, high frequency components which are out of the noise range ate eliminated. Finally, if the image has many components eliminated in the previous step, then its noise estimated value is reduced. Experimental results show that the wavelet filter has better performance than the other high pass filters such as a Laplacian filter, residual from a median filter, residual from a mean filter, and a difference operator. In various images, the algorithm reduces 50% of estimated error on an average.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.591-596
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• 2011

Image denoising is a key issue in all image processing researches. Generally, the quality of an image could be corrupted by a lot of noise due to the undesired conditions of image acquisition phase or during the transmission. Many approaches to image restoration are aimed at removing either Gaussian or impulse noise. Nevertheless, it is possible to find them operating on the same image, which is called mixed noise and it produces a hard damage. In this paper, we proposed noise type classification method and a mixed nonlinear filter for mixed noise suppression. The proposed filtering scheme applies a modified adaptive switching median filter to impulse noise suppression and an efficient nonlinear filer was carried out to remove Gaussian noise. The simulation results based on Matlab show that the proposed method can remove mixed Gaussian and impulse noise efficiently and it can preserve the integrity of edge and keep the detailed information.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.10
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• pp.611-617
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• 2003

A mechanical or electrical stimulation to the mandibular symphysis during a maximal voluntary clenching of the teeth always produces a jaw jerk followed by a silent period (transient stops) in the masseteric EMG (electromyogram). Generally, a mechanical stimulation is followed by a single silent period, and an electrical stimulation is followed by multiple silent periods. In this paper, we propose a new algorithm for determining the duration of the masseter silent period. The decision approach in essentially based upon a segmentation algorithm consisted of variance filter, median filter and gaussian filter. The new adaptive digital notch filter using R-CLMS(reverse constrained least mean-squared) algorithm is proposed for the elimination of powerline(60Hz) noise. At the same time, we design a real time measurement system for the EMG silent period under Window base.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.369-376
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• 2006

The degradation and its inverse modeling can achieve restoration of corrupted image, caused by scaled digitization and electronic transmission. De-speckle process on the noisy document(or SAR) images is one of the basic examples. Non-linearity of the speckle noise model may hinder the inverse process. In this paper, our study is focused on investigation of the restoration methods for bi-level document image degraded by the impulse noise model. Our study shows that, on bi-level document images, the weighted-median filter and the Lee filter methods are very effective among other spatial filtering methods, but wavelet filter method is ineffective in aspect of processing speed: approximately 100 times slower. Optimal values of the weight to be used in the weighted median filter are investigated and presented in this paper.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.10
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• pp.1185-1193
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• 1999

최적 스택 필터는 시그널 또는 영상의 임의의 특성 정보를 보존하고자 하는 요구조건에 의해 강제된 구조적 제약 하에서 최대의 잡음제거 효과를 얻을 수 있다. 그리고 임계치 분할 특성과 양의 부울 함수에 기반한 이진 영역에서의 처리 특성은 이 필터가 높은 병렬성을 갖고 있음을 보여준다. 본 논문에서는 두 개의 병렬 계산 모델 MCC(Mesh-Connected Computer)와 CCC(Cube-Connected Computer)에서 최적 스택 필터를 위한 1차원 병렬 알고리즘을 개발한다. 최적 스택 필터의 실행 시간은 주로 이진 median 연산에 의해 결정되고 본 논문에서 제안된 알고리즘은 선형 분리성에 의해 이 연산을 구현한다. 이를 바탕으로, M 레벨의 1-D 시그널의 길이가 L이고 윈도우 폭이 N이라고 가정할 때, 제안된 알고리즘은 {{{{root M times root M`` MCC에서 O(L sqrt{M}`) 시간에 그리고 M 개의 PE를 갖는 CCC에서 O(L log M)시간에 수행될 수 있다. 또한 잡음을 더욱 효과적으로 제거하기 위해 윈도우 폭 N을 증가시킬 때, 제안된 병렬 알고리즘의 계산 시간은 일정하게 유지됨을 보인다.Abstract An optimal stack filter achieves the maximum noise attenuation under the structural constraints imposed by the requirement of preserving certain signal or image features. And the filter provides a high parallelism due to the principles of threshold decomposition and binary processing based on positive Boolean functions(PBFs). In this paper, we develop an one-dimensional parallel algorithm for the optimal stack filter on two parallel computation models, MCC(Mesh-Connected Computer) and CCC(Cube-Connected Computer). The running time of the optimal stack filter depends mainly on the binary median operation and our algorithm realizes this operation by the linear separability. Based on this scheme, our parallel algorithm can be performed in {{{{O(L sqrt{M}`) MCC and inO(L log M) time on CCC with M PEs, when the length of M``-valued 1-D signal is L`` and window width is N`` Also, we show that the computation time of our parallel algorithm keeps constant when the window width N increases in order to achieve the best noise attenuation.