• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1998년도 Proceedings of International Workshop on Advanced Image Technology
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• pp.165-170
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• 1998

This paper presents a new prediction method RBP region-based prediction model where the context used for prediction contains regions instead of individual pixels. There is a meaningful property that RBP can partition a cartoon image into two distinctive types of regions, one containing full-color backgrounds and the other containing boundaries, edges and home-chromatic areas. With the development of computer techniques, synthetic images created with CG (computer graphics) becomes attactive. Like the demand on data compression, it is imperative to efficiently compress synthetic images such as cartoon animation generated with CG for storage of finite capacity and transmission of narrow bandwidth. This paper a lossy compression method to full-color regions and a lossless compression method to homo-chromatic and boundaries regions. Two criteria for partitioning are described, constant criterion and variable criterion. The latter criterion, in form of a linear function, gives the different threshold for classification in terms of contents of the image of interest. We carry out experiments by applying our method to a sequence of cartoon animation. We carry out experiments by applying our method to a sequence of cartoon animation. Compared with the available image compression standard MPEG-1, our method gives the superior results in both compression ratio and complexity.

• 한국환경보건학회지
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• 제38권2호
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• pp.136-141
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• 2012

Objectives: The objective of this study was to investigate whether the ammonia nitrogen concentration of aqueous samples such as drinking water can be determined by measuring the saturation of the samples colored by indophenol method. Methods: A color saturation measurement system was constructed by connecting a notebook computer to an image acquisition device composed of a PC camera and a light source, and was then used to measure the saturation of samples colored by blue indophenol complex. Results: Between two available light sources, a fluorescent lamp was selected due to its demonstrating better linearity between color saturation and ammonia nitrogen concentration. Prediction by quadratic regression was more accurate than by linear regression, and prediction by quadratic regression in the concentration range of 0.1-1.0 $mg/l$ was more accurate than in the concentration range of 0.0-1.0 $mg/l$. Regression-based predictions over 0.25 $mg/l$, 0.55 $mg/l$ and 0.75 $mg/l$ concentrations were implemented both by spectrophotometric method and by measuring color saturation. In the case of 0.25 $mg/l$, the predicted concentration by spectrophotometric method was $0.256{\pm}0.0076\;mg/l$ and the predicted concentration by measuring color saturation was $0.246{\pm}0.0086\;mg/l$ (p=0.051). In the case of 0.55 $mg/l$, they were $0.561{\pm}0.0068\;mg/l$ and $0.564{\pm}0.0166\;mg/l$ (p=0.660). In the case of 0.75 $mg/l$, they were $0.755{\pm}0.0139\;mg/l$ and $0.762{\pm}0.0088\;mg/l$ (p=0.215). Conclusions: There were no statistically significant differences (p>0.05) between the data from the two methods in all three of the concentrations. Therefore, the color saturation measurement method proposed in this paper may be considered applicable for determining the ammonia nitrogen concentration of aqueous samples such as drinking water.

• 농업과학연구
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• 제47권4호
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• pp.1109-1122
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• 2020

The aim of this study was to develop a marbling classification and prediction model using small parts of sirloin images based on a deep learning algorithm, namely, a convolutional neural network (CNN). Samples were purchased from a commercial slaughterhouse in Korea, images for each grade were acquired, and the total images (n = 500) were assigned according to their grade number: 1++, 1+, 1, and both 2 & 3. The image acquisition system consists of a DSLR camera with a polarization filter to remove diffusive reflectance and two light sources (55 W). To correct the distorted original images, a radial correction algorithm was implemented. Color images of sirloins of Hanwoo (mixed with feeder cattle, steer, and calf) were divided and sub-images with image sizes of 161 × 161 were made to train the marbling prediction model. In this study, the convolutional neural network (CNN) has four convolution layers and yields prediction results in accordance with marbling grades (1++, 1+, 1, and 2&3). Every single layer uses a rectified linear unit (ReLU) function as an activation function and max-pooling is used for extracting the edge between fat and muscle and reducing the variance of the data. Prediction accuracy was measured using an accuracy and kappa coefficient from a confusion matrix. We summed the prediction of sub-images and determined the total average prediction accuracy. Training accuracy was 100% and the test accuracy was 86%, indicating comparably good performance using the CNN. This study provides classification potential for predicting the marbling grade using color images and a convolutional neural network algorithm.

• 방송공학회논문지
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• 제15권4호
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• pp.527-539
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• 2010

대부분의 비디오 부호화 시스템은 YCbCr 색 공간에서 부호화가 수행되나 초고화질 비디오가 사용되는 분야에서는 YCbCr 색 공간에서 부호화하는 것이 RGB 색 공간에서 부호화는 것에 비해 높은 압축 효율을 제공하지 않기 때문에 RGB 공간에서 부호화하는 것이 선호된다. RGB 비디오 신호의 압축 부호화 효율을 증대시키기 위하여 본 논문은 잔여신호의 적응적 주파수-선택 가중 예측 기법을 제안한다. RGB 비디오 신호의 색 평면간 상관도를 최대한 활용하기 위해, 제안 기법은 잔여신호 평면 사이의 주파수 영역에서의 부호 일치도와 상관 강도에 근거하여 적응적으로 잔여신호 평면 간 예측될 주파수 영역과 그에 상응하는 예측 가중치를 선택한다. 실험 결과는 최신의 비디오 압축 표준인 H.264/AVC에서 4:4:4 비디오 부호화의 공통 모드에 비해 약 13% 정도 압축 부호화 성능을 개선시켰음을 보여준다.

• 감성과학
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• 제12권1호
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• pp.109-120
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• 2009

본 연구는 천연염색 직물의 색채로 가장 일반적으로 사용되는 황색과 적색 계열의 색채를 대상으로 색채감성요인의 예측모델을 제시함으로써 색채감성에 영향을 미치는 색채감각과 물리적 색채특성을 규명하고자 하였다. 동일한 견직물에 염색한 서로 다른 320종의 천연염색 색채를 군집 분석하여 선정한 각 4종씩의 황색계열과 적색계열의 색채에 대하여 40대 남녀 30명을 대상으로 의미미분법에 의하여 색채감각 및 감성을 평가하였다. 색채감성용어에 대한 요인분석 결과 3개 요인이 도출되었는데, 요인<활동성>에는 $L^*,\;b^*$, '맑다', '밝다'의 감각과 정적상관을 보여서, 명도가 높고 노랑기가 많은 황색계열 천연염색 직물들이 높은 평가를 받았다. 요인<독특성>은 $a^*$와 '따뜻하다'와 정적 상관을 나타내어서, 적색계열 천연염색 직물들에서 더 강하게 느껴지는 경향을 보였다. 요인<편안성>은 색채감각 '강하다'와 부적 상관을 보였는데, 황색과 적색에 따른 차이가 나타나지 않았다. 각 색채감성요인을 정량화하기 위해 단계적 회귀분석을 통해 수립한 예측모델에서 요인<활동성>은 색채특성 $L^*$ 값이 클수록 더 강하게 인지되어서 무매염 황벽 염색 직물의 색채의 <활동성> 요인점수가 가장 높았으며, 요인<독특성>은 색채특성 $a^*$와 색채감각 '가볍다'가 설명변인으로 진입하여서 $a^*$값이 가장 높은 무매염 홍화300% 염색직물이 <독특성> 감성이 가장 강하게 인지되었다. 또한 요인<편안성>은 색채감각 '강하다'가 부적 설명 변인으로 나타났으며, '강하다'의 점수가 가장 낮은 커피100% 알루미늄 2%매염직물 등의 <편안성> 요인점수가 높게 나타났다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권7호
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• pp.2938-2956
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• 2020

Objective image quality assessment (IQA) models have been developed by effective features to imitate the characteristics of human visual system (HVS). Actually, HVS is extremely sensitive to color degradation and complex texture changes. In this paper, we firstly reveal that many existing full reference image quality assessment (FR-IQA) methods can hardly measure the image quality with contrast and masking texture changes. To solve this problem, considering texture masking effect, we proposed a novel FR-IQA method, called Texture and Color Quality Index (TCQI). The proposed method considers both in the masking effect texture and color visual perceptual threshold, which adopts three kinds of features to reflect masking texture, color difference and structural information. Furthermore, random forest (RF) is used to address the drawbacks of existing pooling technologies. Compared with other traditional learning-based tools (support vector regression and neural network), RF can achieve the better prediction performance. Experiments conducted on five large-scale databases demonstrate that our approach is highly consistent with subjective perception, outperforms twelve the state-of-the-art IQA models in terms of prediction accuracy and keeps a moderate computational complexity. The cross database validation also validates our approach achieves the ability to maintain high robustness.

• 농업과학연구
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• 제47권4호
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• pp.753-767
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• 2020

The commercial value of strawberries is affected by various factors such as their shape, size and color. Among them, size determined by weight is one of the main factors determining the quality grade of strawberries. In this study, image technology was developed to predict the weight of strawberries using the shape characteristics of strawberry cultivars. For realtime weight measurements of strawberries in transport, an image measurement system was developed for weight prediction with a charge coupled device (CCD) color camera and a conveyor belt. A strawberry weight prediction algorithm was developed for three cultivars, Maehyang, Sulhyang, and Ssanta, using the number of pixels in the pulp portion that measured the strawberry weight. The discrimination accuracy (R2) of the weight prediction models of the Maeyang, Sulhyang and Santa cultivars was 0.9531, 0.951 and 0.9432, respectively. The discriminative accuracy (R2) and measurement error (RMSE) of the integrated weight prediction model of the three cultivars were 0.958 and 1.454 g, respectively. These results show that the 2D imaging technology considering the shape characteristics of strawberries has the potential to predict the weight of strawberries.

• 소성∙가공
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• 제19권3호
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• pp.145-151
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• 2010

In case of thin-wall two-color injection molding, flashing often occurs when molten polymer flows into small gap at the parting line in mold with high pressure or under the unbalanced clamping force condition. In this study, flashing was examined in the production of thin-wall notebook case with large area when the rapid heat cycle molding (RHCM) technology was applied to the two-color injection molding. The effects of the RHCM technology on the part properties and weld-lines were compared with conventional injection molding. The flashing caused by the clamping device of the two-color injection molding machine was examined and compared by experiments and CAE analyses.

• 제어로봇시스템학회논문지
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• 제16권4호
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• pp.368-373
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• 2010

A new indoor mobile robot localization method is presented. Robot recognizes well designed single color landmarks on the ceiling by vision system, as reference to compute its precise position. The proposed likelihood prediction based method enables the robot to estimate its position based only on the orientation of landmark.The use of single color landmarks helps to reduce the complexity of the landmark structure and makes it easily detectable. Edge based optical flow is further used to compensate for some landmark recognition error. This technique is applicable for navigation in an unlimited sized indoor space. Prediction scheme and localization algorithm are proposed, and edge based optical flow and data fusing are presented. Experimental results show that the proposed method provides accurate estimation of the robot position with a localization error within a range of 5 cm and directional error less than 4 degrees.

• 한국의류학회지
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• 제45권1호
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• pp.180-199
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• 2021

This study investigated natural aroma fragrance on the fashion image of Galchon, a traditional natural dyeing textile made with immature persimmon from the Jeju area, Korea. Nine fabric pairs consisting of differently colored cotton and silk Galchon with various tones and fabric types were used for subjective evaluation. Thirty five female college students evaluated the specimens using a 7-point scale questionnaire for fashion image-related adjectives. A specimen with three different presentation types that included fabric without fragrance (FO), fabric with citrus fragrance, and fabric with chamaecyparis (FCP) were randomly provided to a subject. As a result, color variables of Galchon were found to be the primary influence on fashion images for both cotton and silk Galchon that showed interaction effects with presentation types. The citrus fragrance increased the feeling of 'Active' while chamaecyparis tended to contribute to a stronger perception of 'Elegance' for cotton Galchon. Finally, these results were used to develop prediction models for fashion images of Galchon that employed color variables and presentation types.