• 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.

• Computers and Concrete
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• v.10 no.2
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• pp.135-147
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• 2012

At mesoscale, concrete is considered as a three-phase composite material consisting of the aggregate particles, the cement matrix and the interfacial transition zone (ITZ). The reconstruction of the internal structures for concrete composites requires the identification of the boundary of the aggregate particles and the cement matrix using digital imaging technology followed by post-processing through MATLAB. A parameter study covers the subsection transformation, median filter, and open and close operation of the digital image sample to obtain the optimal parameter for performing the image processing technology. The subsection transformation is performed using a grey histogram of the digital image samples with a threshold value of [120, 210] followed by median filtering with a $16{\times}16$ square module based on the dimensions of the aggregate particles and their internal impurity. We then select a "disk" tectonic structure with a specific radius, which performs open and close operations on the images. The edges of the aggregate particles (similar to the original digital images) are obtained using the canny edge detection method. The finite element model at mesoscale can be established using the proposed image processing technology. The location of the crack determined through the numerical method is identical to the experimental result, and the load-displacement curve determined through the numerical method is in close agreement with the experimental results. Comparisons of the numerical and experimental results show that the proposed image processing technology is highly effective in reconstructing the internal structures of concrete composites.

• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1585-1601
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• 2017

With the rapid development of computer technologies, a number of image modification methods have emerged, which have great impacts on the security of image information. Therefore, it is necessary to protect the integrity and authenticity of digital images, and digital watermarking technique consequently becomes a research hotspot. An effort is made to survey and analyze advancements of image watermarking algorithms based on singular value decomposition (SVD) in recent years. In the first part, an overview of watermarking techniques is presented and then mathematical theory of SVD is given. Besides, SVD watermarking model, features, and evaluation indexes are demonstrated. Various SVD-based watermarking algorithms, as well as hybrid watermarking algorithms based on SVD and other transforms for copyright protection, tamper detection, location, and recovery are reviewed in the last part.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.1118-1121
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• 2010

With the advent of cell phone digital cameras, and sophisticated photo editing software, digital images can be easily manipulated and altered. Although good forgeries may leave no visual clues of having been tampered with, they may, nevertheless, alter the underlying statistics of an image. Most digital camera equipped in cell phones employ a single image sensor in conjunction with a color filter array (CFA), and then interpolates the missing color samples to obtain a three channel color image. This interpolation introduces specific correlations which are likely to be destroyed when tampering with an image. We quantify the specific correlations introduced by CFA interpolation, and describe how these correlations, or lack thereof, can be automatically detected in any portion of an image. We show the efficacy of this approach in revealing traces of digital tampering in lossless and lossy compressed color images interpolated with several different CFA algorithms in test cell phones.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.114-117
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• 2000

In this paper, we proposed robust digital image watermarking based on modulation transfer function (MTF) of human visual system (HVS). Using the proposed method, robust watermarking is possible both in common image processing operations such as cropping and lossy compression and in geometrical transforms such as rotation, scaling, and translation, because it can embed watermark and template signal maximally using MTF of HVS. Experimental results show that the proposed watermarking method is more robust to several common image processing operations and geometrical transforms.

• Imaging Science in Dentistry
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• v.44 no.1
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• pp.31-35
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• 2014

Purpose: This study was performed to investigate the effect of image enhancement of periapical radiographs according to the diagnostic task. Materials and Methods: Eighty digital intraoral radiographs were obtained from patients and classified into four groups according to the diagnostic tasks of dental caries, periodontal diseases, periapical lesions, and endodontic files. All images were enhanced differently by using five processing techniques. Three radiologists blindly compared the subjective image quality of the original images and the processed images using a 5-point scale. Results: There were significant differences between the image quality of the processed images and that of the original images (P< 0.01) in all the diagnostic task groups. Processing techniques showed significantly different efficacy according to the diagnostic task (P< 0.01). Conclusion: Image enhancement affects the image quality differently depending on the diagnostic task. And the use of optimal parameters is important for each diagnostic task.

• Restorative Dentistry and Endodontics
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• v.27 no.2
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• pp.113-121
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• 2002

Conventional intraoral radiography continues to be the most widely used image modality for the diagnosis of dental caries. But, conventional intraoral radiography has several shortcomings, including the difficulty of exposing and processing intraoral film of consistently acceptable quality. In addition, radiographic retaking that was the result of processing errors, may result in increased discomfort and radiation dose to the patient. Recently, various digital radiographies substitute for conventional intraoral radiography to overcome these disadvantages. The advantages of digital radiography are numerous. One of advantages Is the elimination of processing errors. In addition, the radiation dose for digital system is approximately 20% to 25% of that required for conventional intraoral radiography Another potential advantage of digital imaging is the ability to perform image quality enhancements such as contrast and density modulation, which may increase diagnostic accuracy. The purpose of this study was to compare the diagnostic ability of artificial proximal defects to conventional intraoral radiography, direct digital image(CDX2000HQ$^{\circledR}$) and indirect digital image(Digora$^{\circledR}$). Artificial defects were made in proximal surfaces of 60 extracted human molars using #1/2, #1, #2 round bur. Five dentists assessed proximal defects on conventional intraoral radiography, direct digital image(CDX2000HQ$^{\circledR}$) and indirect digital image(Digora$^{\circledR}$). ROC(Receiver Operating Characteristic) analysis and Two-way ANOVA test were used for the evaluation of detectability, and following results were acquired. 1. The mean ROC area of conventional intraoral radiography, direct digital image(CDX2000HQ$^{\circledR}$) and indirect digital Image(Digora$^{\circledR}$) were 0.6766, 0.7538, 0.6791(Grade I), 0.7176, 0.7594, 0.7361(Grade II), and 0.7449, 0.7608, 0.7414(Grade III), respectively. 2. Diagnostic ability of direct digital image was higher than other image modalities. But, there was no statistically significant difference among other imaging modalities for Grade I, II, III lesion(p>0.05). In conclusion, when direct and indirect digital system are comparable with conventional intraoral radiography. these systems may be considered an alternative of conventional intraoral radiography for the diagnosis of proximal surface caries.

• Computers and Concrete
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• v.5 no.1
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• pp.61-74
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• 2008

Digital image processing algorithms for the analysis and characterization of grains and voids in cemented materials were developed using toolbox functions of a mathematical software package. Utilization of grayscale, color and watershed segmentation algorithms and their performances were demonstrated on artificially prepared self-compacting concrete (SCC) samples. It has been found that color segmentation was more advantageous over the gray scale segmentation for the detection of voids whereas the latter method provided satisfying results for the aggregate grains due to the sharp contrast between their colors and the cohesive matrix. The watershed segmentation method, on the other hand, appeared to be very efficient while separating touching objects in digital images.

• Smart Structures and Systems
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• v.17 no.6
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• pp.935-956
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• 2016

With the help of advanced image acquisition and processing technology, the vision-based measurement methods have been broadly applied to implement the structural monitoring and condition identification of civil engineering structures. Many noncontact approaches enabled by different digital image processing algorithms are developed to overcome the problems in conventional structural dynamic displacement measurement. This paper presents three kinds of image processing algorithms for structural dynamic displacement measurement, i.e., the grayscale pattern matching (GPM) algorithm, the color pattern matching (CPM) algorithm, and the mean shift tracking (MST) algorithm. A vision-based system programmed with the three image processing algorithms is developed for multi-point structural dynamic displacement measurement. The dynamic displacement time histories of multiple vision points are simultaneously measured by the vision-based system and the magnetostrictive displacement sensor (MDS) during the laboratory shaking table tests of a three-story steel frame model. The comparative analysis results indicate that the developed vision-based system exhibits excellent performance in structural dynamic displacement measurement by use of the three different image processing algorithms. The field application experiments are also carried out on an arch bridge for the measurement of displacement influence lines during the loading tests to validate the effectiveness of the vision-based system.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10b
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• pp.871-874
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• 2000

디지털 카메라(Digital Camera)와 같은 휴대형 영상 입력 장치(Portable Image Input Device)는 스캐너 (Scanner)와 달리 3 차원의 피사체(Object)를 디지털 영상으로 생성할 수 있고 다양한 조명 환경(Illuminant)에서 사용할 수 있다는 이유로 많은 응용 분야에서 활발하게 사용되고 있다. 그러나, 정확한 색 재현(Color Reproduction)을 위한 기존의 디지털 카메라 특성화 방법(Digital Camera Characterization Method)은 생성된 영상의 조명 정보를 고려하지 않은 상태에서 색 변환 행렬을 생성하므로 다양한 조명 환경 변화에 대해 적응적으로 대처하지 못하는 단점이 있다. 본 논문에서는 디지털 카메라가 생성하는 영상의 rgb 색도를 이용하여 색도 평면에 색도 다각형(Chromaticity Polygon)을 구성하고 각 색도 다각형들간의 포함 관계에 따라 조명 정보를 평가함으로써 조명색(Illuminant Color)의 변화에 따른 인간 시각 시스템(Human Visual System)의 색 불변성(Color Constancy)을 재현할 수 있는 디지털 카메라 특성화 방법을 제안한다.