• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.407-408
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• 2006

In this paper, we propose a new reversible image authentication technique based on watermarking where if the image is authentic, the distortion due to embedding can be completely removed from the watermarked image after the hidden data has been extracted. This technique utilizes histogram characteristics of the difference image and modifies pixel values slightly to embed more data than other reversible data hiding algorithm. The proposed scheme is quite simple and the execution time is rather short. Experimental results demonstrate that the proposed scheme can detect any modifications of the watermarked image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2817-2834
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• 2016

The existing reversible data hiding methods for block truncation coding (BTC) compressed images often utilize difference expansion or histogram shifting technique for data embedment. Although these methods effectively embed data into the compressed codes, the embedding operations may swap the numerical order of the higher and lower quantization levels. Since the numerical order of these two quantization levels can be exploited to carry additional data without destroying the quality of decoded image, the existing methods cannot take the advantages of this property to embed data more efficiently. In this paper, we embed data by shifting the higher and lower quantization levels in opposite direction. Because the embedment does not change numerical order of quantization levels, we exploit this property to carry additional data without further reducing the image quality. The proposed method performs no-distortion embedding if the payload is small, and performs reversible data embedding for large payload. The experimental results show that the proposed method offers better embedding performance over prior works in terms of payload and image quality.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1708-1714
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• 2010

In this paper, the full color LED billboard or a general quality improvement methods of quality gamma correction, brightness, and brightness adjustment, etc., regardless of the overall color of images uniformly bright or dark have been taken care of. The video itself, but simply expressed as a uniform brightness of a certain size, how to adjust the brightness of input video signal does not reflect the characteristics of the entire screen with just a lighter or darker line is only feeling was brought. So, unlike conventional video transmission system with new LED display technology in the histogram analysis of image data is input by the input image data by determining the luminance values of the attributes are reflected, as appropriate based on the histogram of the distribution of brightness values By controlling the LED display is expressed in the uniform image can improve the brightness control, histogram distribution of the image as full color billboards driven processing technology is proposed.

• Journal of KIISE:Software and Applications
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• v.27 no.4
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• pp.402-411
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• 2000

It is an important step in video indexing and retrieval to detect shot boundaries on video data. Some approaches are proposed to detect shot changes by computing color histogram differences or the variances of DCT coefficients. However, these approaches do not consider the content or meaningful features in the image data which are useful in high level video processing. In particular, it is desirable to detect these features from compressed video data because this requires less processing overhead. In this paper, we propose a new method to detect shot boundaries from MPEG data using region flow and color information. First, we reconstruct DC images and compute region flow information and color histogram differences from HSV quantized images. Then, we compute the points at which region flow has discontinuities or color histogram differences are high. Finally, we decide those points as shot boundaries according to our proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4643-4660
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• 2014

Integrity authentication of biometric data in Wireless Body Area Network (WBAN) is a critical issue because the sensitive data transmitted over broadcast wireless channels could be attacked easily. However, traditional cryptograph-based integrity authentication schemes are not suitable for WBAN as they consume much computational resource on the sensor nodes with limited memory, computational capability and power. To address this problem, a novel lightweight integrity authentication scheme based on reversible watermark is proposed for WBAN and implemented on a TinyOS-based WBAN test bed in this paper. In the proposed scheme, the data is divided into groups with a fixed size to improve grouping efficiency; the histogram shifting technique is adopted to avoid possible underflow or overflow; local maps are generated to restore the shifted data; and the watermarks are generated and embedded in a chaining way for integrity authentication. Our analytic and experimental results demonstrate that the integrity of biometric data can be reliably authenticated with low cost, and the data can be entirely recovered for healthcare applications by using our proposed scheme.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.41-47
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• 2019

In this paper, we propose a application of conditional generative adversarial network (cGAN) for generation of contrast enhanced computed tomography (CT) image. Two types of CT data which were the enhanced and non-enhanced were used and applied by the histogram equalization for adjusting image intensities. In order to validate the generation of contrast enhanced CT data, the structural similarity index measurement (SSIM) was performed. Prepared generated contrast CT data were analyzed the statistical analysis using paired sample t-test. In order to apply the optimized algorithm for the lymph node cancer, they were calculated by short to long axis ratio (S/L) method. In the case of the model trained with CT data and their histogram equalized SSIM were $0.905{\pm}0.048$ and $0.908{\pm}0.047$. The tumor S/L of generated contrast enhanced CT data were validated similar to the ground truth when they were compared to scanned contrast enhanced CT data. It is expected that advantages of Generated contrast enhanced CT data based on deep learning are a cost-effective and less radiation exposure as well as further anatomical information with non-enhanced CT data.

• The Journal of the Korea Contents Association
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• v.18 no.3
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• pp.299-308
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• 2018

This study focused on the fact that medical images that are issued at different hospitals may affect image quality on PACS when different software is used. A university hospital image was copied to the DICOM file and registered on the PACS of the university hospital B. The capacity and image quality of the software used in the university hospital were evaluated by SNR, CNR and histogram. As the compression ratio increased, SNR and CNR tended to decrease. Note that Lossless Compression decreased the data size by half compared to No Compression, but SNR and CNR did not change. As a result of the histogram analysis, the information loss due to the underflow phenomenon was conspicuous. When moving to another hospital, No compression or lossless compression method should be used. In conclusion, it is useful to use the lossless compression method, considering waiting time and economic efficiency in uploading.

• Journal of KIISE:Databases
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• v.35 no.6
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• pp.544-554
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• 2008

Histograms are popularly used for selectivity estimation in database systems. In conventional histogram methods, buckets return the approximated results based on the assumption that all objects in a bucket are uniformly distributed. However, the objects within the region of a query are not likely to be uniformly distributed. That is, there can be some skews (i.e., clusters) in the buckets, which may significantly degrade the accuracy of the histogram. The aim of this work is to enhance the accuracy of histograms. For this purpose, we propose a new two-dimensional histogram method considering clusters. The proposed method detects dense regions and exploits them for organizing buckets. Since the proposed method effectively reduces accuracy degradation caused by clusters, it can provide improved, robust accuracy against skewed data distributions. Through experiments, we show that the proposed method provides up to 74% improved performance compared with the conventional histogram.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.6
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• pp.14-20
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• 2009

The goal of image processing is to improve the visual appearance of images for human viewers. The histogram is an important tool which can be used as basic data of digital image processing. Therefore, to effectively manage a histogram in digital image processing is very important. Currently machine vision systems are used in many appearance inspection fields instead of inspection by human. However, the appearance inspection result by machine vision system is mainly influenced by illumination of workplace. In this paper, we propose a histogram transform method for improving accuracy of machine visual inspection. The enhancement effect of area feature is obtained by performing proposed histogram transformation in area that needs improvement The proposed algorithm is verified by appearance inspection of jig plate samples.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.617-625
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• 2017

In this paper, an effective reversible data embedding algorithm was proposed to embed secrete data into image. In the proposed algorithm, prediction image is generated by accurately predicting pixel values using local similarity existing in image, difference sequence is generated using the generated prediction image and original cover image, and then histogram shift technique is applied to create a stego-image with secrete data hidden. Applying the proposed algorithm, secrete data can be extracted from the stego-image and the original cover image can be restored without loss. Experimental results show that it is possible to embed more secrete data into cover image than APD algorithm by applying the proposed algorithm.