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

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.24 no.2
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• pp.439-450
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• 1994

Recently, the digital image was introduced into radiological image. The digital image has the power of contrast enhancement, histogram control, and other digitally enhancement. At the point of the resolution, periapical radiograph is superior to the digital image, but enhanced digital procedure improves the diagnostic ability of the digital image. The purpose of this study was to evaluate the diagnostic ability of artificial proximal caries in conventional radiographs, digital radiographs and enhanced digital radiographs (histogram specification). ROC (Receiver Operating Characteristic) analysis and paired t-test were used for the evaluation of detectability, and following results were acquired: 1. The mean ROC area of conventional radiographs was 0.9274. 2. The mean ROC area of unenhanced digital image was 0.9168. 3. The mean ROC area of enhanced digital image was 0.9339. 4. The diagnostic ability of three imaging methods was not significant difference(p>0.05). So, the digital images had similar diagnostic ability of artificial proximal caries to conventional radiographs. If properly enhanced digital image, it may be superior to conventional radiographs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.8
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• pp.1813-1819
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• 2011

In this research, the location positioning system supposed is concerned with range recognition technology using phase and magnitude of radio wave and adding technology of image histogram by vision. By the proposed technology, we design the radio transmitter and receiver and realize the measurement system, and save the data in disk that is earned from 900Mhz RF signal, middle frequency 450Khz of analog signal. Range information is earned the data through digital signal processing of IF signal. For the estimation of range measured, we analyze the difference between real range and measurement range, and also suggest the method to improve the measurement error using average processing and amplitude properties.

• Fire Science and Engineering
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• v.22 no.1
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• pp.68-75
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• 2008

In this paper, we introduce a fire-detection system which is robust to light sources and environment changing. We can decide the threshold values that classify the regions between a fire flame and light sources by analyzing them in RGB color space. But we could not discriminate quasi-flame region from fire flame region with the value. The difference of mean-histogram technique make it possible to extract flame region more efficient because fire flame is continuously changing after it occurs. In order to validate real fire, this paper uses regional compactness in the end of process. Computer simulation show that proposed method make more robust to light sources and environment changing.

• The Journal of the Korea Contents Association
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• v.4 no.3
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• pp.91-97
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• 2004

Difference image scheme is widely used for motion estimation in moving object tracking system. This scheme contains a binarization step which segments image into background and moving object regions, referring to threshold value. In this paper, we propose a decision algorithm of tracking the threshold value with a differential image. The key idea is analyzing the histogram of the differential image. In addition we evaluate the performance of this method in comparison with conventional scheme. As an experimental result with 60 images, it is found that threshold by the proposed algorithm is very close to optimal threshold selected manually.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4043-4064
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• 2021

Night-time image quality evaluation is an urgent requirement in visual inspection. The lighting environment of night-time results in low brightness, low contrast, loss of detailed information, and colour dissonance of image, which remains a daunting task of delicately evaluating the image quality at night. A new blind quality assessment metric is presented for realistic night-time scenario through a comprehensive consideration of contrast, texture, and colour in this article. To be specific, image blocks' color-gray-difference (CGD) histogram that represents contrast features is computed at first. Next, texture features that are measured by the mean subtracted contrast normalized (MSCN)-weighted local binary pattern (LBP) histogram are calculated. Then statistical features in Lαβ colour space are detected. Finally, the quality prediction model is conducted by the support vector regression (SVR) based on extracted contrast, texture, and colour features. Experiments conducted on NNID, CCRIQ, LIVE-CH, and CID2013 databases indicate that the proposed metric is superior to the compared BIQA metrics.

• Progress in Medical Physics
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• v.27 no.4
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• pp.203-212
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• 2016

Dose differences between three-dimensional (3D) and four-dimensional (4D) doses could be varied according to the geometrical relationship between a planning target volume (PTV) and an organ at risk (OAR). The purpose of this study is to evaluate the correlation between the overlap volume histogram (OVH), which quantitatively shows the geometrical relationship between the PTV and OAR, and the dose differences. 4D computed tomography (4DCT) images were acquired for 10 liver cancer patients. Internal target volume-based treatment planning was performed. A 3D dose was calculated on a reference phase (end-exhalation). A 4D dose was accumulated using deformation vector fields between the reference and other phase images of 4DCT from deformable image registration, and dose differences between the 3D and 4D doses were calculated. An OVH between the PTV and selected OAR (duodenum) was calculated and quantified on the basis of specific overlap volumes that corresponded to 10%, 20%, 30%, 40%, and 50% of the OAR volume overlapped with the expanded PTV. Statistical analysis was performed to verify the correlation with the OVH and dose difference for the OAR. The minimum mean dose difference was 0.50 Gy from case 3, and the maximum mean dose difference was 4.96 Gy from case 2. The calculated range of the correlation coefficients between the OVH and dose difference was from -0.720 to -0.712, and the R-square range for regression analysis was from 0.506 to 0.518 (p-value <0.05). However, when the 10% overlap volume was applied in the six cases that had OVH value ${\leq}2$, the average percent mean dose differences were $34.80{\pm}12.42%$. Cases with quantified OVH values of 2 or more had mean dose differences of $29.16{\pm}11.36%$. In conclusion, no significant statistical correlation was found between the OVH and dose differences. However, it was confirmed that a higher difference between the 3D and 4D doses could occur in cases that have smaller OVH value.

• The Journal of the Korea Contents Association
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• v.2 no.2
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• pp.17-26
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• 2002

In this paper, we suggest a method to acquire the moving object centered video by panning and tilting a camera automatically according to motion vectors calculated by detecting the motion of a moving object on video steam. We create a difference image by estimating the intensity difference at the grid points of neighboring frames. And we detect the motion using both horizontal projection histogram and vertical projection histogram and decide the center of motion part. Then we calculate a new direction and degree of the motion by comparing coordinates at the center of current motion and the center of previous motion. By controling the RCM using these Motion vectors, we can get video stream positioned unwire object on the center of video frame. Through the experiments, we could get a moving object centered video stream continuously arid monitor remotely by implementing sever/client architecture based on the web.

• Journal of the Korea Convergence Society
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• v.8 no.5
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• pp.19-28
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• 2017

In this paper, we propose a method to reduce the difference in image characteristics when multiple camera images are captured for virtual space production. Sixty-four images were used by cross-mounting eight bodies and lenses, respectively. Image analysis compares and analyzes the standard deviation of the histogram and pixel distribution values. As a result of the analysis, it shows different image characteristics depending on the lens or image sensor, though it is a camera of the same model. In this paper, we have adjusted the distribution of the overall brightness value of the image to compensate for this difference. As a result, the average deviation was the maximum of (Indoor: 6.89, outdoor: 24.23), we obtained images with almost no deviation (Indoor: maximum 0.42, outdoor: maximum: 2.73). In the future, we will study and apply more accurate image analysis methods than image brightness distribution.