• Journal of the Korean Geotechnical Society
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• v.38 no.5
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• pp.61-71
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• 2022

Soil color is used to determine soil classification and its physical, chemical, and biological properties. Visual determination is the most commonly used method for identifying soil color. However, it is subjective and, in many cases, non-repeatable. Digital image processing obtains useful information from digital images, accelerates soil classification, and enables the rapid identification of soil types in a field. This study develops a digital image processing-based soil color analysis technology that can consider irregular light conditions in the field. The digital image studio was designed to simulate the characteristics of natural light (illuminance and color temperature). Also, digital images of two soil samples (Jumoonjin sand and Anseong weathered soil) were captured under 12 different light conditions. For the RGB and CIELAB color systems, soil color intensities of 24 images were obtained using digital image processing. CIELAB was suitable for dealing with irregular light conditions in the field.

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1741-1749
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• 2017

In commercial digital-cameras, color-filter filters light according to wavelength range of color filter array (CFA) and the filtered intensities contain color information of light. Then, output data of CFA is transformed to final rendered image through demosaicing process. In image processing of digital-camera, the quality of the final rendered image is affected by optical cross talk of CFA, kind of CFA pattern etc. Basically, pattern of CFA plays important role in image quality of final image rendered by digital-camera. Therefore, an evaluation system capable of quantitatively evaluating CFA is needed. This paper proposes a novel evaluation system using existing and proposed image metrics for evaluating CFAs of digital-camera. Proposed CFA evaluation system consist of color difference in CIELAB and S-CIELAB, Structure SImilarity (SSIM), MTF50, moire starting point (MSP), and subjective preference (SP). MSP and SP are newly designed for the proposed evaluation system. Proposed evaluation system is expressed in polar coordinates to analyze the characteristics of CFA objectively and intuitively. Through simulations, we confirmed that proposed CFA evaluation system can objectively assess performance of developed CFAs.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.22 no.6
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• pp.131-140
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• 2017

As video equipments such as CCTV are used for various purposes in fields of society, digital video data processing technology such as automatic motion detection is essential. In this paper, we proposed and implemented a more stable and accurate motion detection system based on background subtraction technique. We could improve the accuracy and stability of motion detection over existing methods by efficiently processing color information of digital image data. We divided the procedure of color information processing into each components of color information : brightness component, color component of color information and merge them. We can process each component's characteristics with maximum consideration. Our color information processing provides more efficient color information in motion detection than the existing methods. We improved the success rate of motion detection by our background update process that analyzed the characteristics of the moving background in the natural environment and reflected it to the background image.

• Science of Emotion and Sensibility
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• v.5 no.3
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• pp.11-20
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• 2002

There are Two new models developed for objective evaluation of fabric color patterns by applying a multiple regression analysis and an adaptive foray-rule-based system. The physical features of fabric color patterns are extracted through digital image processing and the emotional features are collected based on the psychological experiments of Soen[3, 4]. The principle physical features are hue, saturation, intensity and the texture of color patterns. The emotional features arc represented thirteen pairs of adverse adjectives. The multiple regression analyses and the adaptive fuzzy system are used as a tool to analyze the relations between physical and emotional features. As a result, both of the proposed models show competent performance for the approximation and the similar linguistic interpretation to the Soen's psychological experiments.

• Proceedings of the KSLP Conference
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• 1998.11a
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• pp.192-193
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• 1998

Introduction : Laryngeal lesions were observed using the OLYMPUS EVIS-200 electronic videoendoscope system attached to the OLYMPUS ENF-200 rhinolarynx endoscope portion. This endoscope portion can be introduced into the laryngeal cavity by inserting it through the nasal passages. Since it is also possible to connect the OLYMPUS EVIP-230 digital image processor capable of processing dynamic images in real time to this system, an attempt has also been made to process the dynamic color images of laryngeal lesions obtained with the electronic videoendoscope system. Structure enhancement and color enhancement were peformed as processing images. The images of laryngeal lesions obtained with this system and the processed images are presented and described from the standpoint of diagnostic usefulness (omitted)

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.3
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• pp.65-70
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• 2000

In general, the quality of agricultural products is determined by direct measurement of a weight or a magnitude, and it is determined by indirect or non-destructive method. In this paper, using color image processing, the algorithm to determine its quality and grading is presented. And the algorithm is applied to real-time citrus classifier. In the system, the size and color of orange are measured by not the sight of human but the digital image processing. The citrus classification system has the real-time maximum classification capacity of six quantify per one second. The system can be applied to controller design for the quality classification of agricultural products.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.1
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• pp.8-16
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• 2012

An image obtained from a low light environment results in a low-exposure problem caused by non-ideal camera settings, i.e. aperture size and shutter speed. Of particular note, the multiple color-filter aperture (MCA) system inherently suffers from low-exposure problems and performance degradation in its image classification and registration processes due to its finite size of the apertures. In this context, this paper presents a novel method for the color enhancement of low-exposure images and its application to color shift model-based MCA system for image refocusing. Although various histogram equalization (HE) approaches have been proposed, they tend to distort the color information of the processed image due to the range limits of the histogram. The proposed color enhancement algorithm enhances the global brightness by analyzing the basic cause of the low-exposure phenomenon, and then compensates for the contrast degradation artifacts by using an adaptive histogram specification. We also apply the proposed algorithm to the preprocessing step of the refocusing technique in the MCA system to enhance the color image. The experimental results confirm that the proposed method can enhance the contrast of any low-exposure color image acquired by a conventional camera, and is suitable for commercial low-cost, high-quality imaging devices, such as consumer-grade camcorders, real-time 3D reconstruction systems, digital, and computational cameras.

• Journal of Multimedia Information System
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• v.6 no.2
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• pp.99-106
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• 2019

In traditional Chinese medical (TCM) science, tongue images can be observed for medical diagnosis; however, the tongue diagnosis of TCM is influenced by the subjective factors of doctors, and the diagnosis results vary from person to person. Quantitative TCM tongue diagnosis can improve the accuracy of diagnosis and increase the application value. In this paper, digital image processing and pattern recognition technologies are employed on mobile device to classify tongue images collected in different health states. First, through grayscale integral projection processing, the trough is found to localize the tongue body. Then the tongue body image is transferred from RGB color space to HSV color space, and the average H and S values are considered as the color features. Finally, the diagnosis results are obtained according to the relationship between the color characteristics and physical symptoms.

• 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.