• IEIE Transactions on Smart Processing and Computing
• /
• v.3 no.6
• /
• pp.358-365
• /
• 2014

This paper proposes a method that reduces the flickering effect caused by A-GLG (Adaptive Gray-Level Grouping) during video contrast enhancement. Of the GLG series, A-GLG shows the best contrast enhancement performance. The GLG series is based on histogram grouping. Histogram grouping is calculated differently between the continuous frames with a similar histogram and causes a subtle change in the transformation function. This is the reason for flickering effect when the video contrast is enhanced by A-GLG. To reduce the flickering effect caused by A-GLG, the proposed method calculates a modified transformation function. The modified transformation function is calculated using a previous and current transformation function applied with a weight separately. The proposed method was compared with A-GLG for flickering effect reduction and video contrast enhancement. Through the experimental results, the proposed method showed not only a reduced flickering effect, but also video contrast enhancement.

• Journal of Korea Society of Industrial Information Systems
• /
• v.20 no.2
• /
• pp.45-56
• /
• 2015

In this paper we propose a very rapid moving object tracking method for an object-based auto focus on a smart phone camera. By considering the limit of non-learning approach on low-performance platforms, we use a sliding-window detection technique based on histogram features. By adapting the integral histogram, we solve the problem of the time-consuming histogram computation on each sub-window. For more speed up, we propose a local candidate search, and an adaptive scaling template method. In addition, we propose to apply a stabilization term in the matching function for a stable detection location. In experiments on our dataset, we demonstrated that we achieved a very rapid tracking performance demonstrating over 100 frames per second on a PC environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.5
• /
• pp.205-211
• /
• 2012

By using an adaptive threshold and weight based on the wavelet transform and Haar transform, a novel image enhancement algorithm is proposed. First, a medical image was decomposed with wavelet transform and all high-frequency sub-images were decomposed with Haar transform. Secondly, noise in the frequency domain was reduced by the proposed soft-threshold method. Thirdly, high-frequency coefficients were enhanced by the proposed weight values in different sub-images. Then, the enhanced image was obtained through the inverse Haar transform and wavelet transform. But the pixel range of the enhanced image is narrower than a normal image. Lastly, the image's histogram was stretched by nonlinear histogram equalization. Experiments showed that the proposed method can be not only enhance an image's details but can also preserve its edge features effectively.

• Journal for History of Mathematics
• /
• v.17 no.2
• /
• pp.15-20
• /
• 2004

We investigate the unbiasedness and consistency as the statistical properties of density estimators. We show histogram, kernel density estimation, and local adaptive smoothing as density smoothing in this paper. Also, the early and recent research on nonparametric density estimation is described and discussed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2001.12a
• /
• pp.279-282
• /
• 2001

This paper presents an image contrast enhancement technique for improving the low contrast images using the improved IAFC(Integrated Adaptive Fuzzy Clustering) Model. The low pictorial information of a low contrast image is due to the vagueness or fuzziness of the multivalued levels of brightness rather than randomness. Fuzzy image processing has three main stages, namely, image fuzzification, modification of membership values, and image defuzzification. Using a new model of automatic crossover point selection, optimal crossover point is selected automatically. The problem of crossover point selection can be considered as the two-category classification problem. The improved MEC can classify the image into two classes with unsupervised teaming rule. The proposed method is applied to some experimental images with 256 gray levels and the results are compared with those of the histogram equalization technique. We utilized the index of fuzziness as a measure of image quality. The results show that the proposed method is better than the histogram equalization technique.

• Journal for History of Mathematics
• /
• v.19 no.3
• /
• pp.113-122
• /
• 2006

We investigate the mathematical background, statistical methodology, and the teaching of computer-software field using smoothing methodology in this paper. Also we investigate conception and methodology of histogram, kernel density estimator, adaptive kernel estimator, bandwidth selection based on mathematics and statistics.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2000.05a
• /
• pp.352-355
• /
• 2000

In this paper, we propose an adaptive thresholding for edge detection. first, we got histograms for background image and image with moving object, respectively. Then we make difference histogram between histograms of background and object image. A thresholding value is decided using gradient of peak to peak in the difference histogram. The experimentation is processed using a moving car in the road. The result is that edge is detected well regardless of the brightness.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2008.05a
• /
• pp.84-87
• /
• 2008

본 논문에서는 Q.Wang & R.K.Ward 가 제안한 WTHE(weighted and thresholded histogram equalization)방법의 enhancement parameters를 주어진 영상의 히스토그램 분포에 따라 적응적으로 제공하는 방법을 제안한다. WTHE는 영상의 히스토그램을 weight와 threshold를 이용하여 변형한 후 히스토그램 평활화(histogram equalization : HE)방법을 수행 함으로써 화질을 개선하는 방법이다. 이 방법은 두 가지 parameters 제어로 기존의 히스토그램 평활화 방법의 단점인 과도한 밝기 변화와 불필요한 artifacts를 줄일 수 있다. 본 논문에서는 WTHE 방법을 좀 더 간편하면서 다양한 분야에 적용하기 위해서 입력 영상에 따라 달라지는 parameters 값을 자동으로 제공하는 적응형 WTHE(Adaptive WTHE : AWTHE) 방법을 제안하고, 제안된 방법의 성능을 실험으로 제시한다.

• Proceedings of the IEEK Conference
• /
• 2001.06d
• /
• pp.101-104
• /
• 2001

This paper proposes a unique shot boundary detection algorithm for the video indexing and/or browsing. Conventional methods based on the frame differences and the histogram differences are improved. Instead of using absolute frame differences, block by block based relative frame differences are employed. Frame adaptive thresholding values are also employed for the better detection. for the cases that the frame differences are not enough to detect the shot boundary, histogram differences are selectively applied. Experimental results show that the proposed algorithm reduces both the “false positive” errors and the “false negative” errors especially for the videos of dynamic local and/or global motions

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.4
• /
• pp.856-873
• /
• 2011

Reversible watermarking is an open problem in information hiding field, with embedding the encoded bit '1' or '0' into some sensitive images, such as the law enforcement, medical records and military images. The technique can retrieve the original image without distortion, after the embedded message has been extracted. Histogram-based scheme is a remarkable breakthrough in reversible watermarking schemes, in terms of high embedding capacity and low distortion. This scheme is lack of capacity control due to the requirement for embedding large-scale data, because the largest hidden capacity is decided by the amount of pixels with the peak point. In this paper, we propose a reversible watermarking scheme to enlarge the number of pixels with the peak point as large as possible. This algorithm is based on an adaptive edge-guided interpolation, furthermore, hides messages by interpolation-error, i.e. the difference between the original and interpolated image value. Simulation results compared with other state-of-the-art reversible watermarking schemes in this paper demonstrate the validity of the proposed algorithm.