• Journal of Biosystems Engineering
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• v.24 no.1
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• pp.67-74
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• 1999

A prototype cut-flower sorter was developed and tested for its performance with five varieties of roses. Support plates driven by a chain mechanism transported the roses into an image inspection chamber. Color image processing algorithms were developed to evaluate the length, thickness, and straightness of stem and color, height, and maturity of bud. The average absolute errors of the system for the measurements of stem length, stem thickness, and height of bud were 19.7 mm, 0.5 mm, and 3.8 mm, respectively. The results of classification by the sorter were compared with those of a human inspector for straightness of stem and maturity of bud. The classification error for the straightness of stem was 8.6%, when both direct image and reflected image by a mirror were analyzed. The accuracy in classifying the maturity of bud varied among the varieties, the smallest for‘Nobless’(1.5%) and the largest for‘Rote Rose’(13.5%). The time required to process a rose averaged 2.06 seconds, equivalent to the capacity of 1,600 roses per hour.

• Journal of ILASS-Korea
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• v.29 no.2
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• pp.91-97
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• 2024

When investigating the droplet, spray, and impact of liquid on a solid plate, backlight imaging has been widely used to understand these phenomena. However, some previous studies have suffered from poor image quality. In this study, various combinations of image processing algorithms, such as white image correction, histogram equalization, CLAHE, Otsu's binarization, and multi-Otsu's binarization, have been applied to flash boiling spray images to enhance image quality for qualitative observation and semi-quantitative spray angle evaluation. To acquire images with high contrast for qualitative observation, applying CLAHE was effective, making small droplets and detailed shapes of the jet noticeable. However, when images were averaged to determine spray angle or penetration length based on intensity, this method induced artifact unphysical patterns, thus requiring careful consideration. Based on the algorithm proposed in this study, the spray angle variation according to injection pressure and temperature has been calculated, showing a reasonable trend.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.243-246
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• 2004

In this paper, we have proposed the contrast control method using brightness preserving on the FPD(Flat Panel Display). The proposed algorithms consist of three blocks: the contrast enhancement, the white-level-expander, and the black-level-expander. The proposed method has employed probability density function in order to control the brightness of the image changed extremely. In order for real-time processing, we have calculated cumulative density function using the linear approximation method. The image histogram and image quality were compared with the conventional image enhancement algorithms. The proposed methods have been used in display devices that need image enhancement such as LCD TV, PDP, and FPD.

• Journal of Broadcast Engineering
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• v.3 no.2
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• pp.111-117
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• 1998

Due to independent processing of image block, DCT-based block coding algorithms can produce the blocking effect qhich is gray-level discontinuity along block boundaries of the reconstructed image. In this paper, we have proposed two techniques to reduce the blocking effect: two-stage transform coding with variable quantizer and the globally optimum filtering. We have also compared performances of our algorithms and other conventional algorithms by applying optimal allocation.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.344-353
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• 2012

In this paper, we propose a super-resolution algorithm using discrete wavelet transform. In general super-resolution algorithms for single-image, probability based operations have been used for searching high-frequency components. Consequently, the complexity of the algorithm causes the increase of processing time. In the proposed algorithm, we use discrete wavelet transform to find high-frequency sub-bands. We perform inverse discrete wavelet transform using input image and high-frequency sub-bands of the same resolution as the input image which are obtained by performing discrete wavelet transform without down-sampling and then we obtain image with high-resolution. In the proposed algorithm, we use the down-sampled version of the original image ($512{\times}512$) as a test image ($256{\times}256$) to compare the performance of algorithms. Through experimental results, we confirm the improved efficiency of the proposed algorithm comparing with conventional interpolation algorithms and also decreased processing time comparing the probability based operations.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.779-782
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• 2002

본 논문에서는 주성분분석(principal component analysis; 이하 PCA) 및 첨도(Kurtosis)에서의 그레이 블록 거리 알고리즘(grey block algorithms; 이하 GBD)을 이용, 영상간의 거리를 측정하여 어느 정도 영상간의 상대적 식별을 용이하게 하여 영상 분류가 되는지 모의실험을 통하여 확인하고자 한다. 모의실험 결과로부터, PCA에서는 k가 9에서 상대적 식별이 불가능함을 보였고, 첨도에서는 k가 4까지만 블록을 택할 할 수 있음을 모의실험을 통하여 확인할 수 있었다.

• Journal of Korea Multimedia Society
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• v.24 no.9
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• pp.1203-1210
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• 2021

In this paper, we developed the inspection system of electric vehicle pouch battery using image processing. Line scan cameras are used for acquiring the all parts of the pouch battery, and several steps of image processing for extracting significant dimensions(User Required Position) of the battery. In image processing, edge lines, node points, dimension lines, etc. were extracted using Preprocessor, Square Edge Detection, and Size Detection algorithms. This is used to measure the dimensions of the location requested by the user on the pouch battery. For verification of the inspection system, the dimensions of three pouch batteries produced in the same process were measured, and the mean and standard deviation were obtained to confirm the precision.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.589-598
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• 2002

The color measuring/matching expert system is implemented with a new color measuring method that combines intelligent algorithms with image processing techniques. Color measuring part of the proposed system preprocesses the scanned original color input images to eliminate their distorted components by means of the image histogram technique of image pixels, and then extracts RGB(Red, Green, Blue)data among color information from preprocessed color input images. If the extracted RGB color data does not exist on the matching recipe databases, we can measure the colors for the user who want to implement the model that can search the rules for the color mixing information, using the intelligent modeling techniques such as fuzzy inference system and adaptive neuro-fuzzy inference system. Color matching part can easily choose images close to the original color for the user by comparing information of preprocessed color real input images with data-based measuring recipe information of the expert, from the viewpoint of the delta Eformula used in practical process.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.5
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• pp.944-951
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• 2009

In this paper, we use image processing algorithms to detect the defects existed on a welding area automatically. It is difficult to detect the welding defects because it is sensitive to lights and has irregular patterns. For this reason, images are captured with 2 kinds of illumination condition, and are processed by 2 different algorithms for each image. The first algorithm separates some ROI's from the captured image and compares the similarity of intensity between each divided region. The second algorithm extracts boundary information from the processed image by the first algorithm, and calculates the length of boundary, curvature and base line area based on boundary information. The proposed method showed high performance in detection and classification of defects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.381-394
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• 2016

The several noise level estimation algorithms that have been developed for use in image processing and computer graphics generally exhibit good performance. However, there are certain special types of noisy images that such algorithms are not suitable for. It is particularly still a challenge to use the algorithms to estimate the noise levels of complex textured photographic images because of the inhomogeneity of the original scenes. Similarly, it is difficult to apply most conventional noise level estimation algorithms to images rendered by the Monte Carlo (MC) method owing to the spatial variation of the noise in such images. This paper proposes a novel noise level estimation method based on histogram modification, and which can be used for more accurate estimation of the noise levels in both complex textured images and MC-rendered images. The proposed method has good performance, is simple to implement, and can be efficiently used in various image-based and graphic applications ranging from smartphone camera noise removal to game background rendition.