• Journal of Korea Multimedia Society
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• v.7 no.9
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• pp.1294-1303
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• 2004

This paper proposes new block fragile watermarking for image authentication and integrity by using the existing pixel-based scheme and block-based scheme. The proposed scheme is performed as fellows. First, we choose LUT(Look Up Table) from each pixel of original image and information of the corresponding block. Next, we insert a watermark, modifying original image with values to compare binary original image with the watermark to be embedded. As a result, we provide the means to overcome some weakness of the existing scheme. Binary logo as watermark can be detected from watermarked image and altered location can also be detected by the unit of pixel or that of block in our scheme.

• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.990-1002
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• 2016

In this paper, we propose a new compression method for the edge image by analyzing the characteristics and the distribution of pixel values of the edge image. The pixel values of the edge image have the Gaussian distribution around '0', and most of the pixel values are `0`. By these analyses we suggest the Zero-Based codec that expresses all values in a CU by a single bit flag. Also, in order to reduce the computational complexity of the proposed codec, the block partition and the intra-prediction techniques are proposed by using edge information like the number of each edge direction, the distribution and the amplitude of a major edge direction in the CU. Experimental results show that the proposed codec leads to a slighter distortion in Y domain than that of HEVC, but has far faster processing speed up to 53 times while it maintains the similar image quality compared to HEVC.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.6
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• pp.523-529
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• 2008

In this paper, we proposed mobile LCD module test device on embedded based, when operating the existing LCD, divide flicker clearly in full frame, and configuration so as to support between other CPU interface, MDDI, SPI, 24Bit RGB interface, etc. that is based on a high-speed CPU. In addition, when demand to test about each pixel of LCD, it is possible to change IP design of H/W, FPGA, but proposed system is application possible without other design changing. Proposed system is made smaller and equipped with battery, so secure with mobility for effective test the LCD/OLED module and it is able to test the pattern by the client program, for example exiting picture, mpeg, simple pattern test and test per pixel, scale, rotation, Odd/Even pixel per video, etc. From now on, if integrating with independent test system and it is configured that is able to mutual communication and test, it is expected to reduce consumption of human resources and improve productivity for LCD module test.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.575-591
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• 2013

Most of the edge detection methods available in literature are gradient based, which further apply thresholding, to find the final edge map in an image. In this paper, we propose a novel method that is based on fuzzy logic for edge detection in gray images without using the gradient and thresholding. Fuzzy logic is a mathematical logic that attempts to solve problems by assigning values to an imprecise spectrum of data in order to arrive at the most accurate conclusion possible. Here, the fuzzy logic is used to conclude whether a pixel is an edge pixel or not. The proposed technique begins by fuzzifying the gray values of a pixel into two fuzzy variables, namely the black and the white. Fuzzy rules are defined to find the edge pixels in the fuzzified image. The resultant edge map may contain some extraneous edges, which are further removed from the edge map by separately examining the intermediate intensity range pixels. Finally, the edge map is improved by finding some left out edge pixels by defining a new membership function for the pixels that have their entire 8-neighbourhood pixels classified as white. We have compared our proposed method with some of the existing standard edge detector operators that are available in the literature on image processing. The quantitative analysis of the proposed method is given in terms of entropy value.

• International Journal of Automotive Technology
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• v.7 no.3
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• pp.361-367
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• 2006

This paper describes a novel stereo vision based localization of free parking site, which recognizes the target position of automatic parking system. Pixel structure classification and feature based stereo matching extract the 3D information of parking site in real time. The pixel structure represents intensity configuration around a pixel and the feature based stereo matching uses step-by-step investigation strategy to reduce computational load. This paper considers only parking site divided by marking, which is generally drawn according to relevant standards. Parking site marking is separated by plane surface constraint and is transformed into bird's eye view, on which template matching is performed to determine the location of parking site. Obstacle depth map, which is generated from the disparity of adjacent vehicles, can be used as the guideline of template matching by limiting search range and orientation. Proposed method using both the obstacle depth map and the bird's eye view of parking site marking increases operation speed and robustness to visual noise by effectively limiting search range.

• Structural Monitoring and Maintenance
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• v.9 no.3
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• pp.289-303
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• 2022

In this study, the impact of assigned pixel labels on the accuracy of crack image identification of steel structures is examined by using an atrous separable convolution neural network (ASCNN). Firstly, images containing fatigue cracks collected from steel structures are classified into four datasets by assigning different pixel labels based on image features. Secondly, the DeepLab v3+ algorithm is used to determine optimal parameters of the ASCNN model by maximizing the average mean-intersection-over-union (mIoU) metric of the datasets. Thirdly, the ASCNN model is trained for various image sizes and hyper-parameters, such as the learning rule, learning rate, and epoch. The optimal parameters of the ASCNN model are determined based on the average mIoU metric. Finally, the trained ASCNN model is evaluated by using 10% untrained images. The result shows that the ASCNN model can segment cracks and other objects in the captured images with an average mIoU of 0.716.

• Current Optics and Photonics
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• v.5 no.4
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• pp.409-420
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• 2021

We propose a method to synthesize a color non-hogel-based computer-generated-hologram (CGH) from light field data of a three-dimensional scene with a hologram pixel pitch shared for all color channels. The non-hogel-based CGH technique generates a continuous wavefront with arbitrary carrier wave from given light field data by interpreting the ray angle in the light field to the spatial frequency of the plane wavefront. The relation between ray angle and spatial frequency is, however, dependent on the wavelength, which leads to different spatial frequency sampling grid in the light field data, resulting in color aberrations in the hologram reconstruction. The proposed method sets a hologram pixel pitch common to all color channels such that the smallest blue diffraction angle covers the field of view of the light field. Then a spatial frequency sampling grid common to all color channels is established by interpolating the light field with the spatial frequency range of the blue wavelength and the sampling interval of the red wavelength. The common hologram pixel pitch and light field spatial frequency sampling grid ensure the synthesis of a color hologram without any color aberrations in the hologram reconstructions, or any loss of information contained in the light field. The proposed method is successfully verified using color light field data of various test or natural 3D scenes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1671-1686
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• 2022

Face manipulation tools represented by Deepfake have threatened the security of people's biological identity information. Particularly, manipulation tools with deep learning technology have brought great challenges to Deepfake detection. There are many solutions for Deepfake detection based on traditional machine learning and advanced deep learning. However, those solutions of detectors almost have problems of poor performance when evaluated on different quality datasets. In this paper, for the sake of making high-quality Deepfake datasets, we provide a preprocessing method based on the image pixel matrix feature to eliminate similar images and the residual channel attention network (RCAN) to resize the scale of images. Significantly, we also describe a Deepfake detector named Cascaded-Hop which is based on the PixelHop++ system and the successive subspace learning (SSL) model. By feeding the preprocessed datasets, Cascaded-Hop achieves a good classification result on different manipulation types and multiple quality datasets. According to the experiment on FaceForensics++ and Celeb-DF, the AUC (area under curve) results of our proposed methods are comparable to the state-of-the-art models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3100-3116
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• 2012

Reversible data hiding enables the embedding of messages in a host image without any loss of host content, which is proposed for image authentication that if the watermarked image is deemed authentic, we can revert it to the exact copy of the original image before the embedding occurred. In this paper, we present an improved histogram-based reversible data hiding scheme based on prediction and sorting. A rhombus prediction is employed to explore the prediction for histogram-based embedding. Sorting the prediction has a good influence on increasing the embedding capacity. Characteristics of the pixel difference are used to achieve large hiding capacity while keeping low distortion. The proposed scheme exploits a two-stage embedding strategy to solve the problem about communicating peak points. We also present a histogram shifting technique to prevent overflow and underflow. Performance comparisons with other existing reversible data hiding schemes are provided to demonstrate the superiority of the proposed scheme.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.4
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• pp.318-324
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• 2017

We introduced a stereo camera on the aircraft to detect flight objects and to estimate the 3D position of them. The Saliency map algorithm based on PCT was proposed to detect a small object between clouds, and then we processed a stereo matching algorithm to find out the disparity between the left and right camera. In order to extract accurate disparity, cost aggregation region was used as a variable region to adapt to detection object. In this paper, we use the detection result as the cost aggregation region. In order to extract more precise disparity, sub-pixel interpolation is used to extract float type-disparity at sub-pixel level. We also proposed a method to estimate the spatial position of an object by using camera parameters. It is expected that it can be applied to image - based object detection and collision avoidance system of autonomous aircraft in the future.