• Journal of the Semiconductor & Display Technology
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• v.13 no.4
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• pp.49-54
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• 2014

This paper proposes a new color segmentation method of vehicle license plates in the RGB color space. Firstly, the proposed method shifts the histogram of an input image rightwards and then stretches the image of the histogram slide. Secondly, the method separates each of the three RGB color components and performs the adaptive threshold processing with the three components, respectively. Finally, it combines the three components under the condition of making up a segment color and removes noises with the morphological processing. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiments were conducted by using real vehicle images. The results show that the proposed algorithm is successful for most vehicle images. However, the method fails in some vehicles when the body and the license plate have the same color.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.313-322
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• 2020

A large volume of data will improve the robustness of deep learning models and avoid overfitting problems. In automatic tongue segmentation, the availability of annotated tongue images is often limited because of the difficulty of collecting and labeling the tongue image datasets in reality. Data augmentation can expand the training dataset and increase the diversity of training data by using label-preserving transformations without collecting new data. In this paper, augmented tongue image datasets were developed using seven augmentation techniques such as image cropping, rotation, flipping, color transformations. Performance of the data augmentation techniques were studied using state-of-the-art transfer learning models, for instance, InceptionV3, EfficientNet, ResNet, DenseNet and etc. Our results show that geometric transformations can lead to more performance gains than color transformations and the segmentation accuracy can be increased by 5% to 20% compared with no augmentation. Furthermore, a random linear combination of geometric and color transformations augmentation dataset gives the superior segmentation performance than all other datasets and results in a better accuracy of 94.98% with InceptionV3 models.

• Journal of the Korean Society of Food Science and Nutrition
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• v.32 no.6
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• pp.806-811
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• 2003

Effects of pH, temperature, light, sugars, organic acids, metal ions, ascorbic acid, thiamine nicotinic acid and pyridoxine on the stability of the color of the cranberry solution were investigated. The pH had marked influences on the color of the cranberry solution: i.e., the color of the cranberry solution was more intense at low pH. It showed characteristic bathochromic shift as the pH of the solution increased. The half-lives of olor value were 34 days at 37$^{\circ}C$, 91 mins at 9$0^{\circ}C$ and 29 mins at 12$0^{\circ}C$. Light gave an adverse effect to the stability of the color. The color degradation can be minimized by shielding the light from the cranberry solution. Among the sugars tested, fructose was the most deleterious followed by sucrose, galactose, maltose and glucose. Fumaric acid was found to be the most effective in stabilizing the color followed by citric acid, malic acid, acetic acid, while tartaric acid was found to be deleterious. Among the metal ions tested N $a^{+}$ and $Mg^{2+}$ were found to be effective in stabilizing the color, while M $n^{2+}$ was found to be the most deleterious followed by F $e^{2+}$, $K^{+}$ and $Ca^{2+}$. Ascorbic acid was found to be deleterious considerably followed by thiamine, while nicotinic acid and pyridoxine were found to be effective in stabilizing the color feebly.or feebly.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.229-232
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• 2005

본 논문에서는 새로운 HAC(Histogram Area Calculation)방법과 영상의 객체분할 방법을 소개한다. 히스토그램을 이용한 영상은 색상 공간의 특징 때문에 조명에 매우 민감하여 빛의 강도에 따라 유사성이 저하되는 경우가 있다. 또한 공간적 정보를 가지고 있지 않아, 전혀 다른 모양의 영상일지라도 칼라 분포가 같은 영상으로 볼 수 있다. 이 논문에서 제안한 방법은 히스토그램 영역을 임의의 영역으로 나눠, 영역들의 유사성을 매칭(matching) 시킨다. 2차 검색방법으로 원 영상에서의 색상 질감 정보가 동일한 영역을 군집화 하여, 영상 분할된 객체들을 이용하여 검색하는 방법이다. 실험 결과, 제안한 방법이 전통적인 히스토그램 방법보다 검색 성능이 효율적인 결과를 얻었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.687-696
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• 2014

This paper presents a semantic object extraction method using user's stroke input, color, and depth information. It is supposed that a semantically meaningful object is surrounded with a few strokes from a user, and has similar depths all over the object. In the proposed method, deciding the region of interest (ROI) is based on the stroke input, and the semantically meaningful object is extracted by using color and depth information. Specifically, the proposed method consists of two steps. The first step is over-segmentation inside the ROI using color and depth information. The second step is semantically meaningful object extraction where over-segmented regions are classified into the object region and the background region according to the depth of each region. In the over-segmentation step, we propose a new marker extraction method where there are two propositions, i.e. an adaptive thresholding scheme to maximize the number of the segmented regions and an adaptive weighting scheme for color and depth components in computation of the morphological gradients that is required in the marker extraction. In the semantically meaningful object extraction, we classify over-segmented regions into the object region and the background region in order of the boundary regions to the inner regions, the average depth of each region being compared to the average depth of all regions classified into the object region. In experimental results, we demonstrate that the proposed method yields reasonable object extraction results.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.769-771
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• 2004

영상을 유사한 특성을 갖는 영역 단위로 분할하는 작업은 다양한 영상 처리를 위한 전처리 과정으로 사용되고 있다. 본 논문에서는 모폴로지(Morphology)와 비선형 확산(Non-Linear Diffusion)을 이용한 영상분할 방법을 제안한다. 초기에 LUV 색상공간에 모폴로지를 응용한 재구성(Reconstruction)에 의한 닫힘(Closing) 연산과 비선형 확산(Non-Linear Diffusion)을 통해 실형 영상을 획득한다 이 영상에서 칼라 영상의 기울기(Gradient) 정보를 획득하고, 마커(Marker) 정보를 이용한 워터쉐드(Watershed) 알고리즘을 적용하여 영상을 효과적으로 분할한다. 그레이 영상과 칼라 영상을 대상으로 한 실험에서 제안 방법이 영상을 효과적으로 분할함을 확인하였다.

• Korean journal of food and cookery science
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• v.16 no.3
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• pp.245-254
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• 2000

The purpose of this study was to provide the basic information for bread with kinds of spice. The qualities of bread added with garlic, ginger, and cinnamon powder were investigated using sensory and mechanical evaluation. The result of sensory evaluation showed that the softness, color, brittleness, hardness, and chewiness of bread were increased as the amount of garlic, ginger and cinnamon powder increased. Lightness decreased by the addition of garlic, ginger and cinnamon powder, while redness and yellowness increased. Texture measurement showed that hardness, cohesiveness, springiness, gumminess and brittleness were the lowest in the breads with 1% garlic, ginger and cinnamon powder, and increased as the added amount of spice increased. A positive correlation was observed between the sensory and mechanical properties in general, while hardness and chewiness have negative correlation with sensory properties. Sensory properties of wheat flour odor, roasted taste, springiness and swelling were positively correlated with the acceptability. Breads with 1% garlic, ginger, and cinnamon powder showed a good overall preference.

• The Journal of the Korea Contents Association
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• v.10 no.7
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• pp.107-114
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• 2010

Color is a sense signal for human to perceive being through light, and the color is divided into chromatic color and achromatic color. Chromatic color has hue, intensity, and saturation, but achromatic color has only intensity among the properties of chromatic color and doesn't have hue and saturation. Therefore it is important to split colors of image into area for human to perceive colors and not to perceive ones based on vision of human being. In this paper, we find a function to split colors of image into chromatic region of chromatic color region and achromatic region of achromatic color region. First, the input image of RGB color space is converted into the image of HSI color space in consideration of human vision and get a binary image from the converted image. After then, a function to split colors into ROC(ROC: Region of chromatic.) and ROA(ROA:Region of achromatic) is yield. It is difficult to split color of a general image into ROC and ROA. Therefore, to get the chromatic area and achromatic area, we make gradient images to have all range of intensity and range of saturation and to have a little range of hue and yield the function. The evaluation is tested using subjective-quality by 50 non-experts for result images of test images and general images. The results of the proposed method get better 27.5~32.96% than these of the conventional method

• Korean Journal of Food Science and Technology
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• v.31 no.4
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• pp.938-944
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• 1999

Response surface methodology (RSM) was used for monitoring the changes of Hunter's color and organoleptic colors of roasted doraji tea with variations in threonine concentration of soaking solution and roasting condition. In soaking and roasting processes based on the central composite design with variations in threonine concentration of soaking solution, roasting temperature and roasting time, coefficients of determinations $(R^{2})$ of the models were above 0.87 (p<0.05) in Hunter's color parameters and organoleptic color. Hunter's color L value of roasted doragi tea was maximized in 0.09% threonine concentration of soaking solution, $142.37^{\circ}C$ and 21.94 min in roasting condition. Hunter's color a value of roasted doragi tea was maximized in 1.24% threonine concentration of soaking solution, $154.01^{\circ}C$ and 28.59 min in roasting condition, minimized in 1.67% threonine concentration of soaking solution, $137.61^{\circ}C$ and 24.62 min in roasting condition, Hunter's color b value of roasted doragi tea was maximized in 1.10% threonine concentration of soaking solution, $154.72^{\circ}C$ and 27.12 min in roasting condition. The maximum quality of organoleptic color of roasted doragi tea was soaked in 1.25% threonine concentration, and roasted at $141.81^{\circ}C$ for 34.14 min.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.3
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• pp.260-272
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• 2001

In this paper, we have designed a region-based image retrieval system, FRIP(Finding Region In the Pictures). This system includes a robust image segmentation scheme using color and texture direction and retrieval scheme based on features of each region. For image segmentation, by using a circular filter, we can protect the boundary of round object and merge stripes or spots of objects into body region. It also combines scaled and shifted color coordinate and texture direction. After image segmentation, in order to improve the storage management effectively and reduce the computation time, we extract compact features from each region and store as index. For user interface, by the user specified constraints such as color-care / don't care. scale-care / dont care, shape-care / dont care and location-care / dont care, the overal/ matching score is estimated and the top Ie nearest images are reported in the ascending order of the final score.