• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4537-4556
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• 2020

This research was based on the study conducted by Khodaei et al. (2012), namely, the least-significant-bit (LSB) substitution combined with the pixel-value differencing (PVD) steganography, and presented an improved irreversible image steganography method. Such a method was developed through integrating the improved LSB substitution with the modulus function-based PVD steganography to increase steganographic capacity of the original technique while maintaining the quality of images. It partitions the cover image into non-overlapped blocks, each of which consists of 3 consecutive pixels. The 2nd pixel represents the base, in which secret data are embedded by using the 3-bit LSB substitution. Each of the other 2 pixels is paired with the base respectively for embedding secret data by using an improved modulus PVD method. The experiment results showed that the method can greatly increase steganographic capacity in comparison with other PVD-based techniques (by a maximum amount of 135%), on the premise that the quality of images is maintained. Last but not least, 2 security analyses, the pixel difference histogram (PDH) and the content-selective residual (CSR) steganalysis were performed. The results indicated that the method is capable of preventing the detection of the 2 common techniques.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.2
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• pp.92-98
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• 2017

Generally, image contains geometrical and radiometric errors. Census transform can solve the stereo mismatching problem caused by the radiometric distortion. Since the general census transform compares center of window pixel value with neighbor pixel value, it is hard to obtain an accurate matching result when the difference of pixel value is not large. To solve that problem, we propose a census transform method that applies different 4-step weight for each pixel value difference by applying an assistance window inside the window kernel. If the current pixel value is larger than the average of assistance window pixel value, a high weight value is given. Otherwise, a low weight value is assigned to perform a differential census transform. After generating an initial disparity map using a weighted census transform and input images, the gradient information is additionally used to model a cost function for generating a final disparity map. In order to find an optimal cost value, we use guided filtering. Since the filtering is performed using the input image and the disparity image, the object boundary region can be preserved. From the experimental results, we confirm that the performance of the proposed stereo matching method is improved compare to the conventional method.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.123-126
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• 2000

In this paper, we propose new watermarking technique using weighting factor decision method in the watermark embedding step and adaptive threshold decision method in the watermark extracting step. In our method, we are determined weighting factor in simple by calculating distance between pixel coefficient and neighborhood pixel coefficients and threshold is adaptively determined by searching the minimized extract error value using histogram of difference value.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.3
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• pp.148-155
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• 2005

A seam-line determination algorithm is proposed to determine image border-line in mosaicing using the transformation of gray value differences and dynamic programming. Since visually good border-line is the one along which pixel differences are as small as possible, it can be determined in association with an optimal path finding algorithm. A well-known effective optimal path finding algorithm is the Dynamic Programming (DP). Direct application of the dynamic programming to the seam-line determination causes the distance effect, in which seam-line is affected by its length as well as the gray value difference. In this paper, an adaptive cost transform algorithm with which the distance effect is suppressed is proposed in order to utilize the dynamic programming on the transformed pixel difference space. Also, a figure of merit which is the summation of fixed number of the biggest pixel difference on the seam-line (SFBPD) is suggested as an evaluation measure of seamlines. The performance of the proposed algorithm has been tested in both quantitively and visually on various kinds of images.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.74-76
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• 2010

Digital images or videos are used in modern digital devices. The resolution of HDTV in digital broadcasting system is higher than that of previous analog systems. Also, mobile phone with 3G can provide images as well as video streaming services in realtime. In these circumstances, the visual quality of images has become an important factor. We can make image clear by transient improvement process that reduces transient in edges. In this paper, we present an transient improvement algorithm. The proposed algorithm improves edges by making smooth edge to steep edge. Before performing transient improvement algorithm, edge detection algorithm should be operated. Laplacian operator is used in edge detection, and the absolute value of it is used to calculate gain value. Then, local maximum and minimum values are computed to discriminate current pixel value to raise up or pull down. Compensating value that gain value multiplies with the difference between maximum (or minimum) value and current pixel value adds (or subtracts) to current pixel value. That is, improved signal is generated by making the narrow transient of edge. The advantage of proposed algorithm is that it doesn't produce shooting problem like overshoot or undershoot.

• Journal of Internet Computing and Services
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• v.3 no.5
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• pp.51-62
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• 2002

The development of computer technology and the advancement of the technology of information and communications spread the technology of multimedia and increased the use of multimedia data with large capacity, Users can grasp the overall video data and they are able to play wanted video back. To grasp the overall video data it is necessary to offer the list of summarized video data information, In order to search video efficiently on index process of video data is essential and it is also indispensable skill, Therefore, this thesis suggested the effective method about the cut detection of frames which will become a basis of an index based on contents of video image data. This suggested method was detected as the unchanging pixel color intelligence value, classified into diagonal direction. Pixel value of color detected in each frame of video data is stored as A(i, j) matrix-i is the number of frames. j is an image height of frame. By using the stored pixel value as the method of sum of squared difference of color two frames I calculated a specified value difference between frames and detected cut quickly and exactly in case it is bigger than threshold value set in advance, To carry out on experiment on the cut detection of frames comprehensively, I experimented on many kinds of video. analyzing and comparing efficiency of the cut detection system.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.153-160
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• 2014

The Streganography method for digital images has to insert secret data into the image without image distortion. Side match method is that size of secret data is calculated by difference of embedded pixel value and mean value of side pixels. And the secret value is embedded into the embedded pixel. Therefore, the more secret data increases, the more image distortion increases, too. In this paper, we propose the enhanced method that calculates embedded pixel value by difference of secret value and mean value of side pixels. In proposed method, more secret data is embedded and image distortion has to decreases.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.11a
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• pp.259-262
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• 2012

In this paper, we propose a new fast algorithm for effective scene change detection. The proposed algorithm exploits Otsu threshold matching technique, which was proposed earlier. In this method, the current and the reference frames are divided into square blocks of particular size. After doing so, the pixel histogram of each block is generated. According to Otsu method, every histogram distribution is assumed to be bimodal, i.e. pixel distribution can be divided into two groups, based on within-group variance value. The pixel value that minimizes the within-group variance is said to be Otsu threshold. After Otsu threshold is found, the same procedure is performed at the reference frame. If the difference between Otsu threshold of a block in the current frame and co-located block in the reference frame is larger than predefined threshold, then a scene change between those two blocks is detected.

• Journal of the Korea Society of Computer and Information
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• v.21 no.2
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• pp.33-42
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• 2016

In this paper, an advanced reversible data hiding algorithm which takes the advantage of the spatial locality in image was proposed. Natural image has a spatial locality. The pixel value of a natural image is similar to the values of neighboring pixels. So, using the neighboring pixel values, it is possible to precisely predict the pixel value. Frequency increases significantly at the peak point of the difference histogram using the predicted values. Therefore, it is possible to increase the amount of data to be embedded. By using the proposed algorithm, visually high quality stego-image can be generated, the original cover image and the embedded data can be extracted from the stego-image without distortion. The embedding data into the cover image of the proposed algorithm is much lager than that of the previous algorithm. The performance of the proposed algorithm was verified by experiment. The proposed algorithm is very useful for the reversible data hiding.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1383-1390
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• 2012

In this paper, we propose a robust pupil detection method using rank order filter and pixel value difference in facial image. We have detected the potential pupil candidates using rank order filter. Many false pupil candidates found at eyebrow are removed using the fact that the pixel difference is much at the boundary between pupil and sclera. The rest pupil candidates are grouped into pairs. Each pair is verified according to geometric constraints such as the angle and the distance between two candidates. A fitness function is obtained for each pair using the pixel values of two pupil regions, we select a pair with the smallest fitness value as a final pupil. The experiments have been performed for 400 images of the BioID face database. The results show that it achieves more than 90% accuracy, and especially the proposed method improves the detection rate and high accuracy for face with spectacle.