• Korean Journal of Microbiology
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• v.47 no.1
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• pp.50-55
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• 2011

A simple and rapid method was developed for monitoring of Gram-positive bacteria in the wastewater treatment system. Culture suspensions of 4 Gram-positive and 4 Gram-negative strains were filtrated and stained with a polyethersulfone membrane filter and Toluidine Blue-O. To establish quantitative color image analysis, the intensity value of RGB (red-green-blue) color of a scanned filter image was analyzed with a photographic program. Red and green color values of Gram-positive bacteria were higher than those of Gram-negative bacteria. This method was applied to the activated sludge mixed with the Gram-positive bacteria. Although evaluation was difficult due to the irregular size and shape of flocs, the population of Gram-positive bacteria in the activated sludge could be monitored with floc dispersion technique. The more amounts of Gram-positive bacteria in the activated sludge led to the increase of red and green color values. This method provides a rapid and quantitative measurement of Gram-positive bacteria within the wastewater treatment systems.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.127-136
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• 2010

In multi-view video, illumination disharmony between neighboring views can occur on account of different location of each camera and imperfect camera calibration, and so on. Such discrepancy can be the cause of the performance decrease of multi-view video coding by mismatch of inter-view prediction which refer to the pictures obtained from the neighboring views at the same time. In this paper, we propose an efficient histogram-based prefiltering algorithm to compensate mismatches between the luminance and chrominance components in multi-view video for improving its coding efficiency. To compensate illumination variation efficiently, all camera frames of a multi-view sequence are adjusted to a predefined reference through the histogram matching. A Cosited filter that is used for chroma subsampling in many video encoding schemes is applied to each color component prior to histogram matching to improve its performance. The histogram matching is carried out in the RGB color space after color space converting from YCbCr color space. The effective color conversion skill that has respect to direction of edge and range of pixel value in an image is employed in the process. Experimental results show that the compression ratio for the proposed algorithm is improved comparing with other methods.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.569-577
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• 2000

The position of tobacco leaves is affluence to the quality. To evaluate its quality, sample leaves was collected according to the position of attachment. In Korea, the position was divided into four classes such as high, middle, low and inside positioned leaves. Until now, the grade of standard sample was determined by human expert from korea ginseng and tobacco company. Many research were done by the chemical and spectrum analysis using NIR and computer vision. The grade of tobacco leaves mainly classified into 5 grades according to the attached position and its chemical composition. In high and low positioned leaves shows a low level grade under grade 3. Generally, inside and medium positioned leaf has a high level grade. This is the basic research to develop a real time tobacco leaves grading system combined with portable NIR spectrum analysis system. However, this research just deals with position recognition and grading using the color machine vision. The RGB color information was converted to HSI image format and the sample was all investigated using the bundle of tobacco leaves. Quality grade and position recognition was performed through well known general error back propagation neural network. Finally, the relationship about attached leaf position and its grade was analyzed.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.6
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• pp.81-89
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• 2004

In this paper, we compare face recognition rate by PCA algorithm using distance change and embedded data being input left side and right side image in stereo images. The proposed method detects face region from RGB color space to YCbCr color space. Also, The extracted face image's scale up/down according to distance change and extracts more robust face region. The proposed method through an experiment could establish standard distance (100cm) in distance about 30∼200cm, and get 99.05% (100cm) as an average recognition result by scale change. The definition of super state is specification region in normalized size (92${\times}$112), and the embedded data extracts the inner factor of defined super state, achieved face recognition through PCA algorithm. The orignal images can receive specification data in limited image's size (92${\times}$112) because embedded data to do learning not that do all learning, in image of 92${\times}$112 size averagely 99.05%, shows face recognition rate of test 1 99.05%, test 2 98.93%, test 3 98.54%, test 4 97.85%. Therefore, the proposed method through an experiment showed that if apply distance change rate could get high recognition rate, and the processing speed improved as well as reduce face information.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.465-472
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• 2003

For an effective pre-treatment process of a face input image, it is necessary to detect each of face components, calculate the face area, and estimate the rotary angle of the face. A proposed method of this study can estimate an robust result under such renditions as some different levels of illumination, variable fate sizes, fate rotation angels, and background color similar to skin color of the face. The first step of the proposed method detects the estimated face area that can be calculated by both adapted skin color Information of the band-wide HSV color coordinate converted from RGB coordinate, and skin color Information using histogram. Using the results of the former processes, we can detect a lip area within an estimated face area. After estimating a rotary angle slope of the lip area along the X axis, the method determines the face shape based on face information. After detecting eyes in face area by matching a partial template which is made with both eyes, we can estimate Y axis rotary angle by calculating the eye´s locations in three dimensional space in the reference of the face area. As a result of the experiment on various face images, the effectuality of proposed algorithm was verified.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.384-392
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• 2022

The objective of this study was to estimated nitrogen content and chlorophyll using RGB, Hyperspectral sensors to diagnose of nitrogen nutrition in apple tree leaves. Spectral data were acquired through image processing after shooting with high resolution RGB and hyperspectral sensor for two-year-old 'Hongro/M.9' apple. Growth data measured chlorophyll and leaf nitrogen content (LNC) immediately after shooting. The growth model was developed by using regression analysis (simple, multi, partial least squared) with growth data (chlorophyll, LNC) and spectral data (SPAD meter, color vegetation index, wavelength). As a result, chlorophyll and LNC showed a statistically significant difference according to nitrogen fertilizer level regardless of date. Leaf color became pale as the nutrients in the leaf were transferred to the fruit as over time. RGB sensor showed a statistically significant difference at the red wavelength regardless of the date. Also hyperspectral sensor showed a spectral difference depend on nitrogen fertilizer level for non-visible wavelength than visible wavelength at June 10th and July 14th. The estimation model performance of chlorophyll, LNC showed Partial least squared regression using hyperspectral data better than Simple and multiple linear regression using RGB data (Chlorophyll R²: 81%, LNC: 81%). The reason is that hyperspectral sensor has a narrow Full Half at Width Maximum (FWHM) and broad wavelength range (400-1,000 nm), so it is thought that the spectral analysis of crop was possible due to stress cause by nitrogen deficiency. In future study, it is thought that it will contribute to development of high quality and stable fruit production technology by diagnosis model of physiology and pest for all growth stage of tree using hyperspectral imagery.

• Journal of Korea Multimedia Society
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• v.13 no.2
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• pp.316-323
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• 2010

In this paper, we propose fingertip extraction and hand motion recognition method for augmented reality applications. First, an input image is transformed into HSV color space from RGB color space. A hand area is segmented using double thresholding of H, S value, region growing, and connected component analysis. Next, the end points of the index finger and thumb are extracted using morphology operation and subtraction for a virtual keyboard and mouse interface. Finally, the angle between the end points of the index finger and thumb with respect to the center of mass point of the palm is calculated to detect the touch between the index finger and thumb for implementing the click of a mouse button. Experimental results on various input images showed that our method segments the hand, fingertips, and recognizes the movements of the hand fast and accurately. Proposed methods can be used the input interface for augmented reality applications.

• Journal of Korea Multimedia Society
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• v.14 no.8
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• pp.1082-1093
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• 2011

Traditional rendering of cartoon character cannot revive the feeling of concept drawings properly. In this paper, we propose capture technology to get toon shading model from the concept drawings and with this technique, we provide a new novel system to render 3D cartoon character. Benefits of this system is to cartoonize the 3D character according to saliency to emphasize the form of 3D character and further support the sketch-based user interface for artists to edit shading by post-production. For this, we generate texture automatically by RGB color sorting algorithm to analyze color distribution and rates of selected region. In the cartoon rendering process, we use saliency as a measure to determine visual importance of each area of 3d mesh and we provide a novel cartoon rendering algorithm based on the saliency of 3D mesh. For the fine adjustments of shading style, we propose a user interface that allow the artists to freely add and delete shading to a 3D model. Finally, this paper shows the usefulness of the proposed system through user evaluation.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.15-24
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• 2011

Recently various anatomic researches by using serially sectioned images in VK(Visible Korean) project are in progress. In that sense, it is very important and necessary to represent images which keep information of the original anatomic images. In this regard, there are some studies to get rid of slice patterns in coronal and sagittal images. However, according to the rapid spatial frequency changes, the ringing effect occurred in common. In addition, because of merge with the original images which have splice patterns, those patterns appeared again. Therefore, in this study we found effective color space to apply to FFT(Fast Fourier Transform) and notch filter in getting rid of the slice patterns. To verify this, we used RGB, LAB, CMYK, HSV and HSL color space. Secondly we got rid of and alleviated the ringing effect by improving notch filter. To verify this, we compared proposed method with previous study on the basis of original images by visual method and objective values. These result images are expected to contribute to anatomy research in relation to VK project.

• Journal of Advanced Navigation Technology
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• v.17 no.6
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• pp.792-797
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• 2013

4D film is just a film that made by adding some physical effects to 3D film or general film. In order to provide physical effects to the audience, the data that make the physical effect must be added to each frames. In this paper, we proposed a video detection system that can efficiently provide physical effects by assessing the present situation such as explosion scene, snowing scene. The proposed video detection system contains an algorithm for fire detection by using R color and $C_r$ value, and also an algorithm for snow detection by using RGB color model. The system constitutes in a MCU that from 8051 family. In the performance evaluations, the result shows that 91% of detection rate in case of fire and 25% of false detection rate in case of snow. Also the system is capable of providing physical effects automatically.