• Journal of the Semiconductor & Display Technology
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• v.19 no.1
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• pp.6-10
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• 2020

Unlike modern photography technology, in the early days, efforts to physically compose an image with a concept similar to the current photograph have not been popular or commercially successful. The limitation of the use of images as artistic media or recordings has reached the stage of introducing the technology of image analysis to automate the function that humans recognize and judge through vision. In addition, the accuracy of the image has exceeded the human visual ability, enabling the technology that enables the step of recognizing and informing the fact that the human is not aware of it. Based on such a base, the range that can be applied through the image data in the future era can be said to be unpredictable, and the technology that targets large scale image database instead of an image is also expanding the possibilities as a new application technology. In order to identify a particular image from a massive database, different methodologies have been introduced. In this paper, we discuss image identifier production methods based on multi-resolution pyramid.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.93-96
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• 2021

The desire for a technology that can mechanically acquire 2D images starting with the manual method of drawing has been making possible a wide range of modern image-based technologies and applications over a period. Moreover, this trend of the utilization of image-related technology as well as image-based information is likely to continue. Naturally, as like other technology areas, the function that humans produce and utilize by using images needs to be automated by using computing-based technologies. Surprisingly, technology using images in the future will be able to discover knowledge that humans have never known before through the information-related process that enables new perception, far beyond the scope of use that human has used before. Regarding this trend, the manipulation and configuration of massively distributed image database system is strongly demanded. In this paper, we discuss image identifier production methods based on the utilization of the image hashing technique which especially puts emphasis over an entropy operator.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.2
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• pp.35-47
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• 2018

The 4th industrial revolution, digital image technology has developed beyond the limit of multimedia industry to advanced IT fusion and composite industry. Particularly, application technology related to HCI element algorithm in 3D image object recognition field is actively developed. 3D image object recognition technology evolved into intelligent image sensing and recognition technology through 3D modeling. In particular, image recognition technology has been actively studied in image processing using object recognition recognition processing, face recognition, object recognition, and 3D object recognition. In this paper, we propose a research method of human factor 3D image recognition technology applying human factor algorithm for 3D object recognition. 1. Methods of 3D object recognition using 3D modeling, image system analysis, design and human cognitive technology analysis 2. We propose a 3D object recognition parameter estimation method using FACS algorithm and optimal object recognition measurement method. In this paper, we propose a method to effectively evaluate psychological research techniques using 3D image objects. We studied the 3D 3D recognition and applied the result to the object recognition element to extract and study the characteristic points of the recognition technology.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.86-96
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• 2020

Based on the use cases of image recognition technology, this study looked at how artificial intelligence plays a role in image recognition technology. Through image recognition technology, satellite images can be analyzed with artificial intelligence to reveal the calculation of oil storage tanks in certain countries. And image recognition technology makes it possible for searching images or products similar to images taken or downloaded by users, as well as arranging fruit yields, or detecting plant diseases. Based on deep learning and neural network algorithms, we can recognize people's age, gender, and mood, confirming that image recognition technology is being applied in various industries. In this study, we can look at the use cases of domestic and overseas image recognition technology, as well as see which methods are being applied to the industry. In addition, through this study, the direction of future research was presented, focusing on various successful cases in which image recognition technology was implemented and applied in various industries. At the conclusion, it can be considered that the direction in which domestic image recognition technology should move forward in the future.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.463-468
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• 2021

Single image super-resolution (SISR) is an image processing technique, and its main target is to reconstruct the high-quality or high-resolution (HR) image from the low-quality or low-resolution (LR) image. Currently, deep learning-based convolutional neural network (CNN) image super-resolution approaches achieved remarkable improvement over the previous approaches. Furthermore, earlier approaches used hand designed filter to upscale the LR image into HR image. The design architecture of such approaches is easy, but it introduces the extra unwanted pixels in the reconstructed image. To resolve these issues, we propose novel deep learning-based approach known as Lightweight deep CNN-based approach for Single Image Super-Resolution (LDCSIR). In this paper, we propose a new architecture which is inspired by ResNet with Inception blocks, which significantly drop the computational cost of the model and increase the processing time for reconstructing the HR image. Compared with the other state of the art methods, LDCSIR achieves better performance in terms of quantitively (PSNR/SSIM) and qualitatively.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.3
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• pp.288-293
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• 2016

Electronic Image Stabilization(EIS) is widely used as a technique for correcting a shake of an image. The case requiring the EIS function has been increased in high magnification thermal image observation on portable military equipment. Projection Algorithm(PA) for EIS is easy to implement but its performance is sensitive to the projection area. Especially, projection profiles of thermal image have very modest change and are difficult to extract image shifts between frames. In this paper, we proposed algorithm to extract a feature image for the thermal image and compared Block Matching Algorithm(BMA) with PA using our proposed feature image. When using our proposed feature image, BMA was simply implemented using FPGA's internal small memory. And we were able to obtain 30 % PSNR improved results compared to PA.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1078-1099
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• 2021

Traditional image steganography hides secret information by embedding, which inevitably leaves modification traces and is easy to be detected by steganography analysis tools. Since coverless steganography can effectively resist steganalysis, it has become a hotspot in information hiding research recently. Most coverless image steganography (CIS) methods are based on mapping rules, which not only exposes the vulnerability to geometric attacks, but also are less secure due to the revelation of mapping rules. To address the above issues, we introduced camouflage images for steganography instead of directly sending stego-image, which further improves the security performance and information hiding ability of steganography scheme. In particular, based on the different sub-features of stego-image and potential camouflage images, we try to find a larger similarity between them so as to achieve the reversible steganography. Specifically, based on the existing CIS mapping algorithm, we first can establish the correlation between stego-image and secret information and then transmit the camouflage images, which are obtained by reversible sub-feature retrieval algorithm. The received camouflage image can be used to reverse retrieve the stego-image in a public image database. Finally, we can use the same mapping rules to restore secret information. Extensive experimental results demonstrate the better robustness and security of the proposed approach in comparison to state-of-art CIS methods, especially in the robustness of geometric attacks.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.75-80
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• 2002

The mainly used technique to rectify satellite images with distortion is to develop a mathematical relationship between the pixel coordinates on the image and the corresponding points on the ground. By defining the relationship between two coordinate systems, a polynomial model is designed and various linear transformations are used. These GCP based geometric correction has performed overall plane to plane mapping. In the overall plane mapping, overall structure of a scene is considered, but local variation is discarded. The highly variant height of region is resampled with distortion in the rectified image. To solve this problem this paper proposed the TIN-based rectification on a satellite image. The TIN based rectification is good to correct local distortion, but insufficient to reflect overall structure of one scene. So, this paper shows the experimental result and the analysis of each rectification model. It also describes the relationship GCP distribution and rectification model. We can choose a geometric correction model as the structural characteristic of a satellite image and the acquired GCP distribution.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.790-792
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• 2003

The remote sensing image server provides advanced image serving capabilities for geospatial image. Wide seamless image mosaics of Landsat 5 over GMS countries, which exceed a 15 GB or more in size per image, can integrate with other GIS map servers. The approach of two improvement algorithms leads to speed up the response time while preserving the data quality. This system does not only provide images on the web, but also provide GIS layers to WMS client map servers. The advantage of this approach is its efficiency lower cost in terms of cost, time and updating to obtain and utilize remote sensing image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.211-227
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• 2011

Content Based Image Retrieval (CBIR) is an approach for retrieving similar images from an image database based on automatically-derived image features. The quality of a retrieval system depends on the features used to describe image content. In this paper, we propose an image clustering system that takes a database of images as input and clusters them using k-means clustering algorithm taking into consideration color, texture and shape features. Experimental results show that the combination of the three features brings about higher values of accuracy and precision.