• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.39 no.2
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• pp.92-98
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• 2003

The quantification of fish school abundance was carried out by using luminance of pixel on scanning sonar image, and compared with the indices of fish school abundance e.g. school number, school area and weighted school area. The survey was carried out in Funka Bay off southern Hokkaido, Japan using research vessel Ushio-Maru during December 1999. A 180-degree scanning sonar with a frequency of 164kHz was used. The school number was counted both left and right 40-degree radial lines from the center of own vessel mark on a scanning image. The school area was measured approximately as an ellipse from the school length and width. The weighted school area was calculated by multiplying school area and average value of inner pixel luminance. A quantification of pixel luminance was also measured to integrate squared pixel luminance value on these lines. Fish school and school bottom were discriminated by the produced sonar echogram using pixel luminance value on these lines. The relationships between the quantified luminance value and other abundance indices such as school area and weighted school area revealed a good correlation. Therefore, the quantified luminance is a useful method in estimating fish school abundance in the acoustic survey using sonar.

• The Journal of Korean Association of Computer Education
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• v.11 no.5
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• pp.57-66
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• 2008

An adaptive optimization of parametric cubic convolution for image interpolation is derived in this paper. The proposed technique is based on optimizing the standard cubic convolution interpolation formula at each interpolated pixel. Conventional parametric cubic convolution methods use a fixed parameter in an image, so properties of each pixel cannot be incorporated into the interpolation. The proposed method optimizes the interpolation kernel by obtaining parameters adaptively on each pixel. A new cost function is introduced to reflect frequency properties of the original data. The proposed technique produces noticeably sharper edges than traditional techniques and exhibits an average PSNR improvement of traditional techniques.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.3
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• pp.181-193
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• 2010

The paper presents an alternative way to classical stereocorrelation. First, 2D image processing of random patterns is described. Sub-pixel displacements are determined using phase analysis. Then distortion evaluation is presented. The distortion is identified without any assumption on the lens model because of the use of a grid technique approach. Last, shape measurement and shape variation is caught by fringe projection. Analysis is based on two pin-hole assumptions for the video-projector and the camera. Then, fringe projection is coupled to in-plane displacement to give rise to 3D measurement set-up. Metrological characterization shows a resolution comparable to classical (stereo) correlation technique ($1/100^{th}$ pixel). Spatial resolution seems to be an advantage of the method, because of the use of temporal phase stepping (shape measurement, 1 pixel) and windowed Fourier transform (in plane displacements measurement, 9 pixels). Two examples are given. First one is the study of skin properties; second one is a study on leather fabric. In both cases, results are convincing, and have been exploited to give mechanical interpretation.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.666-679
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• 2018

The discrete wavelet transform (DWT) has good multi-resolution decomposition characteristic and its low frequency component contains the basic information of an image. Based on this, a fragile watermarking using the local binary pattern (LBP) and DWT is proposed for image authentication. In this method, the LBP pattern of low frequency wavelet coefficients is adopted as a feature watermark, and it is inserted into the least significant bit (LSB) of the maximum pixel value in each block of host image. To guarantee the safety of the proposed algorithm, the logistic map is applied to encrypt the watermark. In addition, the locations of the maximum pixel values are stored in advance, which will be used to extract watermark on the receiving side. Due to the use of DWT, the watermarked image generated by the proposed scheme has high visual quality. Compared with other state-of-the-art watermarking methods, experimental results manifest that the proposed algorithm not only has lower watermark payloads, but also achieves good performance in tamper identification and localization for various attacks.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.34-46
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• 2019

A method for detecting foreign substances in mould based on scatter grams was presented to protect moulds automatically during moulding production. This paper proposes a wavelet transform foreign detection method based on Monte Carlo analysis mechanism to identify foreign objects in the tube. We use the Monte Carlo method to evaluate the image, and obtain the width of the confidence interval by the deviation statistical gray histogram to divide the image type. In order to stabilize the performance of the algorithm, the high-frequency image and the low-frequency image are respectively drawn. By analyzing the position distribution of the pixel gray in the two images, the suspected foreign object region is obtained. The experiments demonstrate the effectiveness of our approach by evaluating the labeled data.

• Transactions of the Society of Information Storage Systems
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• v.5 no.1
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• pp.36-40
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• 2009

We describe the experimental realization of image system using wavefront coding in 3-Mega pixel mobile phone camera. We designed aspheric lens to extend the depth of field (DOF) using wavefront coding. In addition, through the aspheric lens and lens barrel manufacturing, we obtained a raw image from a camera module. In our method, the acquired images are restored in the spatial frequency domain using the proposed filter and the spatial frequency response (SFR) is calculated. The proposed filters are composed of image denoising filter using low band pass filter in frequency domain and restoration filter for image restoration. Finally, we achieve an enhanced image by super-resolution image processing. Visual examples are given to demonstrate the performance of the proposed filter.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1224-1242
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• 2018

Aiming at motion analysis and compensation, it is essential to conduct motion detection with images. However, motion detection and tracking from low-altitude images obtained from an unmanned aerial system may pose many challenges due to degraded image quality caused by platform motion, image instability and illumination fluctuation. This research tackles these challenges by proposing a modified joint transform correlation algorithm which includes two preprocessing strategies. In spatial domain, a modified fuzzy edge detection method is proposed for preprocessing the input images. In frequency domain, to eliminate the disturbance of self-correlation items, the cross-correlation items are extracted from joint power spectrum output plane. The effectiveness and accuracy of the algorithm has been tested and evaluated by both simulation and real datasets in this research. The simulation experiments show that the proposed approach can derive satisfactory peaks of cross-correlation and achieve detection accuracy of displacement vectors with no more than 0.03pixel for image pairs with displacement smaller than 20pixels, when addition of image motion blurring in the range of 0~10pixel and 0.002variance of additive Gaussian noise. Moreover,this paper proposes quantitative analysis approach using tri-image pairs from real datasets and the experimental results show that detection accuracy can be achieved with sub-pixel level even if the sampling frequency can only attain 50 frames per second.

• Korean Journal of Digital Imaging in Medicine
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• v.9 no.1
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• pp.7-15
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• 2007

This study aim to investigate image characteristics due to focus-grid and head phantom decentering from the armorphos silicon thin film transistor detector the fixed focus-grid is applied, wish to propose right use method of digital medical equipment. Acquired image according to focus-grid and head phantom position decentering using head phantom on armorphos silicon thin film transistor detector the fixed focus-grid is applied. acquired image evaluate pixel value, histogram, plot profile, surface plot using NIB (Image J) image analysis program and compared decentering image with standard image. Mean value and standard deviation value of focus-grid lateral decentering and duplex decentering of focus-grid and head phantom decreased by ratio, consequently increase of horizontality, diagonal decentering. also, deteriorated contrast of image because frequency of high pixel value decreases fairly. according increases decentering, image distortion phenomenon was increase, by next time, pixel mean value of head phantom decentering was no big change but horizontality, diagonal, mean value and standard deviation value of pixel decreased by ratio. Even if increase pixel noise of image because wide latitude and post processing ability of digital detector, radiotechnologist can not recognize. Therefore, radiotechnologist must recognize correctly the photographing factors which increases pixel noise on the grid system installation digital detector and should exam.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.401-403
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• 2019

In this paper, we propose a generative adversarial networks (GAN) based text-to-image generating method. In many natural language processing tasks, which word expressions are determined by their term frequency -inverse document frequency scores. Word2Vec is a type of neural network model that, in the case of an unlabeled corpus, produces a vector that expresses semantics for words in the corpus and an image is generated by GAN training according to the obtained vector. Thanks to the understanding of the word we can generate higher and more realistic images. Our GAN structure is based on deep convolution neural networks and pixel recurrent neural networks. Comparing the generated image with the real image, we get about 88% similarity on the Oxford-102 flowers dataset.

• Journal of information and communication convergence engineering
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• v.13 no.4
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• pp.264-269
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• 2015

The chest X-ray image cannot be focused in the same manner that optical lenses are and the resultant image generally tends to be slightly blurred. Therefore, the methods to improve the quality of chest X-ray image have been studied. In this paper, the inherent noises of the input images are suppressed by adding the Laplacian image to the original. First, the chest X-ray image using an Gaussian high pass filter and an optimal high frequency emphasis filter has shown improvements in the edges and contrast of flat areas. Second, using fuzzy logic_histogram equalization, each pixel of the chest X-ray image shows the normal distribution of intensities that are not overexposed. As a result, the proposed method has shown the enhanced edge and contrast of the images with the noise canceling effect.