• Journal of Korea Society of Industrial Information Systems
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• v.22 no.4
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• pp.1-9
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• 2017

In this Paper, Double Encryption Technology Based on Phase-Shifting Digital Holography and Digital Watermarking is Proposed. For the Purpose, we First Set a Logo Image to be used for Digital Watermark and Design a Binary Phase Computer Generated Hologram for this Logo Image using an Iterative Algorithm. And Random Generated Binary Phase Mask to be set as a Watermark and Key Image is Obtained through XOR Operation between Binary Phase CGH and Random Binary Phase Mask. Object Image is Phase Modulated to be a Constant Amplitude and Multiplied with Binary Phase Mask to Generate Object Wave. This Object Wave can be said to be a First Encrypted Image Having a Pattern Similar to the Noise Including the Watermark Information. Finally, we Interfere the First Encrypted Image with Reference Wave using 2-step PSDH and get a Good Visible Interference Pattern to be Called Second Encrypted Image. The Decryption Process is Proceeded with Fresnel Transform and Inverse Process of First Encryption Process After Appropriate Arithmetic Operation with Two Encrypted Images. The Proposed Encryption and Decryption Process is Confirmed through the Computer Simulations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.431-433
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• 2022

With the development of IoT technology, various technologies such as artificial intelligence and automation are being grafted into industrial sites, and accordingly, the importance of data processing is increasing. Image denoising is one of the basic processes of image processing, and is used as a preprocessing step in many applications. Various studies have been conducted to remove noise, but various problems arise in the process of noise removal, such as image detail preservation, texture restoration, and special noise removal. In this paper, we propose a digital filter using an extended convolutional mask to preserve image detail during the impulse denoising process. The proposed algorithm uses an extended convolution mask as a filtering mask, and obtains the final output by switching the extension level according to the noise level. Simulation was conducted to evaluate the performance of the proposed algorithm, and the performance was analyzed compared to the existing method.

• Korean Journal of Optics and Photonics
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• v.18 no.5
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• pp.303-308
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• 2007

We report here on the application of a digital holographic microscope as a metrology tool for the inspection and the micro-topography reconstruction of different micro-structures of phase shift photo-mask (PSM). The lithography by phase shift photo-mask uses the interference and the pattern of the PSM is not imaged by general optical microscope. The technique allows us to obtain digitally a high-fidelity surface topography description of the phase shift photo-mask with only one hologram image acquisition, allowing us to have relatively simple and compact set-ups able to give quantitative information of PSM.

• Korean Journal of Artificial Intelligence
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• v.9 no.2
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• pp.7-14
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• 2021

Purpose: To solve urban problems, empirical research is being actively conducted to implement a smart city based on various ICT technologies, and digital twin technology is needed to effectively implement a smart city. A digital twin is essential for the realization of a smart city. A digital twin is a virtual environment that intuitively visualizes multidimensional data in the real world based on 3D. Digital twin is implemented on the premise of the convergence of GIS and BIM, and in particular, a lot of time is invested in data pre-processing and labeling in the data construction process. In digital twin, data quality is prioritized for consistency with reality, but there is a limit to data inspection with the naked eye. Therefore, in order to improve the required time and quality of digital twin construction, it was attempted to detect a building using Mask R-CNN, a deep learning-based masking algorithm for aerial images. If the results of this study are advanced and used to build digital twin data, it is thought that a high-quality smart city can be realized.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.630-632
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• 2012

Contemporary society has evolved in the digital information age. Because of this, use of various digital images has been increased. To process these images, various digital image processing methods are used. Edge detection methods, one of those, are utilized to various areas of application such as object recognition, line detection. To detect edge, there are many methods such as Sobel, Prewitt, Laplacian. Because images which are dealt with existing methods are processed in same methods regardless the distribution of gray-level in image, edge detection property is insufficient. Therefore, In this study, to improve shortcomings of existing methods an algorithm using modified expansion mask is proposed.

• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.126-130
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• 2021

The ball grid array is one of the packaging methods that used in high density printed circuit board. Solder void defects caused by voids in the solder ball during the BGA process do not directly affect the reliability of the product, but it may accelerate the aging of the device on the PCB layer or interface surface depending on its size or location. Void inspection is important because it is related in yields with products. The most important process in the optical inspection of solder void is the segmentation process of solder and void. However, there are several segmentation algorithms for the vision inspection, it is impossible to inspect all of images ideally. When X-Ray images with poor contrast and high level of noise become difficult to perform image processing for vision inspection in terms of software programming. This paper suggests the solution to deal with the suggested problem by means of using Mask R-CNN instead of digital image processing algorithm. Mask R-CNN model can be trained with images pre-processed to increase contrast or alleviate noises. With this process, it provides more efficient system about complex object segmentation than conventional system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.9
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• pp.2199-2205
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• 2013

In modern society the image processing has been applied to various digital devices such as smartphone, digital camera, and digital TV. In the field of image processing the edge detection is one of the important parts in the image processing procedure. The image edge means point that the pixel value is changed between background and object rapidly, and includes the important information such as magnitude, location, and orientation. The performance of the existing edge detection method is insufficient for the image degraded by AWGN(additive white Gaussian noise) because it detects edges by using small weighted masks. Therefore, in this paper, to detect edge in AWGN environment effectively, we proposed an algorithm that detects edge as calculated gradient of sorting vector which is transformed by estimated mask from new pixel according to each region.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.214-220
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• 2021

In modern society, various digital communication equipments are being used due to the influence of the 4th industrial revolution, and accordingly, interest in removing noise generated in the data transmission process is increasing. In this paper, we propose a filtering algorithm to remove AWGN generated during digital image transmission. The proposed algorithm removes noise based on mask matching to preserve information such as the boundary of an image, and uses pixel values with similar patterns according to the pattern of the input pixel value and the surrounding pixels for output calculation. To evaluate the proposed algorithm, we simulated with existing AWGN removal algorithms, and analyzed using enlarged image and PSNR comparison. The proposed algorithm has superior AWGN removal performance compared to the existing method, and is particularly effective in images with strong noise intensity of AWGN.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1039-1045
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• 2021

In modern society, due to the influence of the 4th industrial revolution, camera sensors and image-based automation systems are being used in various fields, and interest in image and signal processing is increasing. In this paper, we propose a digital filter algorithm for image reconstruction in an impulse noise environment. The proposed algorithm divides the image into eight masks in vertical, horizontal, and diagonal directions based on the local mask set in the image, and compares the standard deviation of each segmentation mask to obtain a reference value. The final output is calculated by applying the weight according to the spatial distance and the weight using the reference value to the local mask. To evaluate the performance of the proposed algorithm, it was simulated with the existing algorithm, and the performance was compared using enlarged images and PSNR.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.268-270
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• 2013

According to the development and supply of Wibro technology digital technology is applied in several fields. Digital images are damaged by various noises in the process of transfer and storage; the image restoration is to reduce the influence of the noises on images by removing the noises. To make good image restoration several methods have been proposed but the noise removal property is not satisfactory. Therefore, to effectively remove noises noise decision is made and if it is decided as a noise, the size of mask is enlarged; this is adaptive median filter algorithm that is proposed in this paper. And through simulation the superiority of this algorithm to existing methods has been verified.