• 센서학회지
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• 제33권3호
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• pp.179-184
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• 2024

In the car industry, welding is a fundamental linking technique used for joining components, such as steel, molds, and automobile parts. However, accurate inspection is required to test the reliability of the welding components. In this study, we investigate the detection of weld beads using 2D image processing in an automatic recognition system. The sample image is obtained using a 2D vision camera embedded in a lighting system, from where a portion of the bead is successfully extracted after image processing. In this process, the soot removal algorithm plays an important role in accurate weld bead detection, and adopts adaptive local gamma correction and gray color coordinates. Using this automatic recognition system, geometric parameters of the weld bead, such as its length, width, angle, and defect size can also be defined. Finally, on comparing the obtained data with the industrial standards, we can determine whether the weld bead is at an acceptable level or not.

• 한국의상디자인학회지
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• 제7권3호
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• pp.75-81
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• 2005

The experiment aimed at knowing the effect of physiology and psychology according to season on color preference. Two tests, one of the spring and the other of the autumn was conducted. Seventy subjects with normal color vision served as subjects. The subjects entered a bioclimatic chamber controlled at a temperature of $25\pm1^{\circ}C$, a relative humidity of $50\pm5\%$ and a light of 1000 1x. The subjects wearing white shirts and trousers sat quietly on a sofa for one our. Sensation from warm to cool colors might be possibly different individually Therefore, a subject asked to array 41 randomly placed cloth colors from very warm to very cool colors during rest quietly for one our. All subjects arrayed these cloth colors in the order from red through yellow and green to blue, which had the reproducibility. After rest, they were instructed to choose a single one out of 41 cloth colors, preferred by themselves, every 10min during one our 0-ring test were measured to red, yellow, white, blue, black, favorite color, and dislike color. Most subjects preferred warmer color in April than in December. Tympanic temperature was significantly lower in December than in April. Finger presser was significantly higher in like color than in dislike color but it was no significant differences between spring and autumn. The preferring the warm color in April toward summer when basal metabolic rate is decreased than in December toward winter when it is increased can explain that physiology reaction by load error between actual core temperature and set-point induces psychological reaction to pursue visual alliesthesia. Our present experiment revealed that the preferred color could be determined by the relationship between the internal temperature and its set point according to season. It should be emphasized that the alliesthesia was observed also in the realm of visual system.

• 한국축산식품학회지
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• 제40권6호
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• pp.896-907
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• 2020

Imaging technique or computer vision (CV) technology has received huge attention as a rapid and non-destructive technique throughout the world for measuring quality attributes of agricultural products including meat and meat products. This study was conducted to test the ability of CV technology to predict the quality attributes of beef. Images were captured from longissimus dorsi muscle in beef at 24 h post-mortem. Traits evaluated were color value (L*, a*, b*), pH, drip loss, cooking loss, dry matter, moisture, crude protein, fat, ash, thiobarbituric acid reactive substance (TBARS), peroxide value (POV), free fatty acid (FFA), total coliform count (TCC), total viable count (TVC) and total yeast-mould count (TYMC). Images were analyzed using the Matlab software (R2015a). Different reference values were determined by physicochemical, proximate, biochemical and microbiological test. All determination were done in triplicate and the mean value was reported. Data analysis was carried out using the programme Statgraphics Centurion XVI. Calibration and validation model were fitted using the software Unscrambler X version 9.7. A higher correlation found in a* (r=0.65) and moisture (r=0.56) with 'a*' value obtained from image analysis and the highest calibration and prediction accuracy was found in lightness (r²_c=0.73, r²_p=0.69) in beef. Results of this work show that CV technology may be a useful tool for predicting meat quality traits in the laboratory and meat processing industries.

• 대한전자공학회논문지SP
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• 제46권2호
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• pp.89-98
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• 2009

컴퓨터 비전 분야에서 영상 모자이킹 (Image Mosaicking)은 제한된 시야각의 카메라를 사용하여 획득한 여러 장의 중첩된 영역을 가지는 영상을 한 장의 영상으로 정합하여 나타내는 기법이다. 최근에는 연속된 영상에서 카메라의 기학학적인 움직임 때문에 발생하는 영상의 왜곡이나 밝기 차에 관계없이 정확한 정합을 수행하기 위해서 특징점을 기반으로 서술자를 구성하는 정합 방법이 많이 연구되고 있다. 그러나 대부분의 특징점 검출 알고리즘들은 영상의 밝기값 기반의 처리 과정을 수행하기 때문에 영상의 칼라 성분은 다르지만 밝기값이 비슷한 경우, 또는 동영상에서 시간의 흐름에 따라 광원이 변화하는 경우에는 광원의 영향에 따라 검출되는 특징점의 수와 각각의 지역 서술자의 특성이 변하여 정확한 대응점을 검출하는데 오류를 유발하게 된다. 이런 문제점을 해결하기 위해서 본 논문은 영상의 칼라 정보를 이용한 특징점 기반의 영상 모자이킹 방법을 제안하였다. 디지털 칼라 카메라로부터 획득한 디지털 값을 좁은 대역을 갖는 가상의 카메라 출력값으로 변환하여 물체의 분광 반사율 기반의 값으로 유도하고 이것을 광원의 변화에 불변하는 칼라 불변 값 (Color-Invariant Value)으로 정의하였다. 제안된 칼라 불변값의 유효성을 검증하기 위해서 시뮬레이션된 광원들과 Macbeth Color-Checker를 이용하여 확인하였으며, 실험결과에서 제안한 방법과 기존의 SIFT 알고리즘을 비교를 통해 제안된 방법의 정합율의 향상을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2575-2577
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• 2000

We experimented on AGV driving test with color CCD camera which is setup on it. This paper can be divided into two parts. One is image processing part to measure the condition of the guideline and AGV. The other is part that obtains the reference steering angle through using the image processing parts. First, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, AGV knows the driving conditions of AGV. After then using of those information, AGV calculates the reference steering angle changed by the speed of AGV. In the case of low speed, it focuses on the left/right error values of the guide line. As increasing of the speed of AGV, it focuses on the slop of guide line. Lastly, we are to model the above descriptions as the type of PID controller and regulate the coefficient value of it the speed of AGV.

• Journal of Biosystems Engineering
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• 제27권2호
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• pp.133-142
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• 2002

This is a fundamental study to develop a sensor to detect weeds in paddy field using machine vision adopted spectralphotometric technique in order to use the sensor to spread herbicide selectively. A set of spectral reflectance data was collected from dry and wet soil and leaves of rice and 6 kinds of weed to select desirable wavelengths to classify soil, rice and weeds. Stepwise variable selection method of discriminant analysis was applied to the data set and wavelengths of 680 and 802 m were selected to distinguish plants (including rice and weeds) from dry and wet soil, respectively. And wavelengths of 580 and 680 nm were selected to classify rice and weeds by the same method. Validity of the wavelengths to distinguish the plants from soil was tested by cross-validation test with built discriminant function to prove that all of soil and plants were classified correctly without any failure. Validity of the wavelengths for classification of rice and weeds was tested by the same method and the test resulted that 98% of rice and 83% of weeds were classified correctly. Feasibility of CCD color camera to detect weeds in paddy field was tested with the spectral reflectance data by the same statistical method as above. Central wavelengths of RGB frame of color camera were tried as tile effective wavelengths to distingush plants from soil and weeds from plants. The trial resulted that 100% and 94% of plants in dry soil and wet soil, respectively, were classified correctly by the central wavelength or R frame only, and 95% of rice and 85% of weeds were classified correctly by the central wavelengths of RGB frames. As a result, it was concluded that CCD color camera has good potential to be used to detect weeds in paddy field.

• 패션비즈니스
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• 제7권3호
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• pp.14-23
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• 2003

The purpose of this study is to determine affects of hair colors on physical shapes and images through field survey and experimental research. For the purpose, this researcher surveyed 230 female college students residing in Busan about their dyed hair colors, and selected the subjects for the study. Then the researcher an experimental research on the subjects by suing test stimuli. Results of the study can be described as follows: Experiment of the Optical Illusion of Physical Shapes. For all items measured for the experiment, except four ones, if was found that hair colors provided significant efforts of optical illusion factor analysis, included horizontality, outlines of the body and face, a horizontal line of the shoulder, the length, verticality and a horizontal line of the face. According to hair colors, black made the body look slimmer and the face look apparent. White made the body height look low, the outline of the face look clear and the neck or shoulder look fleshed. Female college students whose hair color was orange looked unclear in the body silhouette, bright in the face and broad in the hip and shoulder. Other students whose hair color was red, attracting the line of vision upward most strongly, looked fleshed in the upper body and broad in the face. Finally, blue made the face look dark.

• 자동차안전학회지
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• 제14권2호
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• pp.45-50
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• 2022

The vehicle motion in urban environment is determined by surrounding traffic flow, which cause understanding the flow to be a factor that dominantly affects the motion planning of the vehicle. The traffic flow in this urban environment is accessed using various urban infrastructure information. This paper represents a color recognition algorithm for traffic lights to perceive traffic condition which is a main information among various urban infrastructure information. Deep learning based vision open source realizes positions of traffic lights around the host vehicle. The data are processed to input data based on whether it exists on the route of ego vehicle. The colors of traffic lights are estimated through pixel values from the camera image. The proposed algorithm is validated in intersection situations with traffic lights on the test track. The results show that the proposed algorithm guarantees precise recognition on traffic lights associated with the ego vehicle path in urban intersection scenarios.

• 대한전자공학회논문지SP
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• 제47권2호
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• pp.1-10
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• 2010

디지털 콘텐츠의 응용분야가 확산되면서 디지털 콘텐츠의 색상을 표준화하기 위한 연구가 활발히 진행되고 있다. 따라서 색상을 이용한 영상의 특징을 표현하는 방법도 표준화에 준한 연구가 필요하다. 또한 다양한 응용분야에 사용될 수 있는 색상 특징을 추출하는 방법도 필요하다. 본 논문에서는 디지털 표색계의 근간이 되는 먼셀좌표계를 기본으로 하여 기준색상을 50색상으로 정의하고 영상 내 색상의 분포 특성을 알 수 있는 히스토그램을 구하고 영상을 대표할 수 있는 대표색상을 추출한다. 제안 방법의 성능을 평가하기 위해 18개의 실험영상을 만들어 기존의 방법과 제안방법을 적용하였으며 일반영상에도 적용하여 그 결과를 분석하였다. 제안방법을 적용한 결과영상은 영상 내에 존재하는 색상의 분포 특성을 잘 나타내주며 대표색상으로 빈도가 집중함으로 영상의 대표색상을 이용하여 다양한 응용분야에 적용이 가능하다.

• 사물인터넷융복합논문지
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• 제10권2호
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• pp.51-60
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• 2024

저조도 환경에서 영상 이미지의 콘트라스트가 낮고 식별이 어려운 문제를 목표로 사람의 시각 감지 기반의 콘트라스트 적응 보상 증진 알고리즘을 제안한다. 첫째, 저조도 환경에서 평균 밝기, 평균 대역폭 요인의 영상 이미지 특징 요인을 추출하고, 원본 영상의 회색/색도 차이에 따라 사람의 시각적 콘트라스트 해상도 보상의 수학적 모델을 설정하며, 실제 컬러의 3원색에 대해 각각 비례 적분하여 보상한다. 다음으로 보상 정도가 명시각 차이를 적절하게 구별할 수 있는 것보다 낮을 때 보상 임계값 선형 보상이 명시각에서 전체 대역폭으로 설정된다. 마지막으로 주관적인 이미지 품질 평가와 이미지 특성 요인을 결합하여 비례 계수를 보상하는 자동 최적화 모델을 구축한다. 실험 테스트 결과는 영상 이미지 적응 증진 알고리즘이 우수한 증진 효과와 우수한 실시간 성능을 가지며 다크 비전 정보를 효과적으로 마이닝할 수 있으며 다양한 시나리오에서 널리 사용될 수 있음을 보여준다.