• The Journal of Korea Robotics Society
• /
• v.17 no.3
• /
• pp.245-254
• /
• 2022

Sensor dataset for autonomous driving is one of the essential components as the deep learning approaches are widely used. However, most driving datasets are focused on typical environments such as sunny or cloudy. In addition, most datasets deal with color images and lidar. In this paper, we propose a driving dataset with multi-spectral images and lidar in adverse weather conditions such as snowy, rainy, smoky, and dusty. The proposed data acquisition system has 4 types of cameras (color, near-infrared, shortwave, thermal), 1 lidar, 2 radars, and a navigation sensor. Our dataset is the first dataset that handles multi-spectral cameras in adverse weather conditions. The Proposed dataset is annotated as 2D semantic labels, 3D semantic labels, and 2D/3D bounding boxes. Many tasks are available on our dataset, for example, object detection and driveable region detection. We also present some experimental results on the adverse weather dataset.

• The Journal of the Acoustical Society of Korea
• /
• v.30 no.3
• /
• pp.142-148
• /
• 2011

The final aim of the present study is to develop the intelligent robot, emulating human synesthetic skills which make it possible to associate a color image with a specific sound. This can be done on the basis of the mutual conversion between color image and sound. As a first step of the final goal, this study focused on a basic system using a conversion of color image into sound. This study describes a proposed method to convert color image into sound, based on the likelihood in the physical frequency information between light and sound. The method of converting color image into sound was implemented by using HSI histograms through RGB-to-HSI color model conversion, which was done by Microsoft Visual C++ (ver. 6.0). Two different color images were used on the simulation experiments, and the results revealed that the hue, saturation and intensity elements of each input color image were converted into fundamental frequency, harmonic and octave elements of a sound, respectively. Through the proposed system, the converted sound elements were then synthesized to automatically generate a sound source with wav file format, using Csound.

• Journal of Digital Contents Society
• /
• v.9 no.2
• /
• pp.245-250
• /
• 2008

Psychology of color is a research field of psychology for studying human's behavior connected with color. Color carries symbolism and image while sharing psychological consensus with human. Each color has a respective image such as hope, passion, love, life, death, and so on. Peculiar stimuli by colors on these images have great influence on human's emotion and psychology. We therefore proposed a method for understanding human's state of emotion based on colors in this paper. In order to understand human's state of emotion, we analyzed color information used to model a room by a user and then described frequencies of each color as percent using fuzzy inference rules by membership values of fuzzy membership functions for colors used for modeling the room. When we applied the proposed color-based emotion analysis method to emotional state based on colors of Alschuler and Hattwick, we could see the proposed method is efficient.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.33 no.7
• /
• pp.1003-1013
• /
• 2009

This study offers data that can be used to direct the styles of black dresses by looking into the characteristics of coordination in black fashion, which is continuously appearing at modem. fashion collections with a unique aesthetic value and image. This study examined the characteristic of fashion coordination of black color: First, to look at the fashion image of black color, second, to look at the characteristic of black color coordination appearing in black fashion, and third, to look at the method of coordination appearing in black color. This study collected and selected 560 black pictures that showed the fashion collections from 2005 S/S until 2007 F/W. As for data analysis, the researcher made a content analysis by classifying the pictures by item, material, accessory, and a coordination method. The research results are as follows: First, the fashion image of black color was expressed as sexy feminine, modern chic, modern future, genderless, and avant-garde images. Second, the fashion coordination of black color has the characteristics of sexiness and dignity by the use of body exposure, concealment, and a subdued line that expresses a modern, minimal atmosphere. The mix & match of materials expressed the monotony of one color as refined beauty and the use of accessories appeared to bring the image into relief. Third, as for the coordination method, pants on skirts, pants on dresses, piece coordination of code matching, plus- one coordination through vivid colors and accessories, and cross-over coordination relying on shape, material, and sense were prominent.

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

• The Journal of Korean Medicine
• /
• v.37 no.3
• /
• pp.27-38
• /
• 2016

Objectives: According to Korean Medicine theory, the skin color of LU10 serves as a diagnostic clue to dyspeptic symptoms. The aims of this study were (1) to find the difference of skin color in LU10 region between functional dyspepsia (FD) and healthy control (HC) and (2) to examine the relationship between LU10 skin color parameters and dyspeptic symptoms. Methods: 39 participants (29 FD and 10 HC) have participated in this study. They were asked to complete gastrointestinal scale (GIS), gastrointestinal symptom rating scale (GSRS), Nepean dyspepsia index (NDI), functional dyspepsia-related quality of life (FD-QoL), visual analogue scale (VAS) for dyspeptic symptoms, food retention questionnaire (FRQ) and cold heat questionnaire (CHQ). $L^*$ (luminance), $a^*$ (red-green balance) and $b^*$ (yellow-blue balance) values of LU10 region were calculated through digital images of the participant's hand. Then we evaluated test-retest reliability of $L^*$, $a^*$ and $b^*$ values of LU10 region. Additionally, we compared $L^*$, $a^*$ and $b^*$ values of LU10 between FD and HC, and examined the relationship between LU10 color parameters and seven questionnaires scores. Results: Only $L^*$ values in LU10 region were significantly higher in FD compared with HC. GIS scores and the subset scores of NDI had a positive correlation with $L^*$ values significantly. Correlation coefficients of test-retest reliability of skin color measurement of LU10 ranged from 0.871 to 0.936 representing very strongly statistically significant (P<0.001). Conclusions: We confirmed the difference of skin color in LU10 region between FD and HC, and relationship between LU10 skin color parameters and dyspeptic symptoms.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.9C
• /
• pp.930-938
• /
• 2005

We propose a content-based image retrieval(CBIR) method based on an efncient combination of a color feature and multiresolution texture features. As a color feature, a HSV autocorrelograrn is chosen which is blown to measure spatial correlation of colors well. As texture features, BDIP and BVLC moments are chosen which is hewn to measure local intensity variations well and measure local texture smoothness well, respectively. The texture features are obtained in a wavelet pyramid of the luminance component of a color image. The extracted features are combined for efficient similarity computation by the normalization depending on their dimensions and standard deviation vectors. Experimental results show that the proposed method yielded average $8\%\;and\;11\%$ better performance in precision vs. recall than the method using BDIPBVLC moments and the method using color autocorrelograrn, respectively and yielded at least $10\%$ better performance than the methods using wavelet moments, CSD, color histogram. Specially, the proposed method shows an excellent performance over the other methods in image DBs contained images of various resolutions.

• Journal of KIISE:Software and Applications
• /
• v.36 no.12
• /
• pp.986-995
• /
• 2009

Color affects people in their various combinations of hue, saturation and value. On the other hand, people may feel different emotion from the same color. If we can introduce these characteristics of color and people's emotion about color to emotion-based digital technologies and their contents, we can effectively draw users' interest and immersion to the contents. In this paper, we will show how people feel about color and present a method of image coloring that reflects the user's preference. First, we define basic templates that reflect the relationship between color and emotion, and then perform an image coloring. To reflect user's preference, we compute weights for hue, saturation and value through the experiments on each subject's preference about hue, saturation and value. The image coloring for each subject's taste will be drawn by updating the weights of hue, saturation and value. Through the results of experiments and surveys, we found that people were more satisfied with the transformation of the templates which reflected user's preference than the one that did not.

• The Journal of the Korea Contents Association
• /
• v.6 no.2
• /
• pp.44-50
• /
• 2006

This study has proposed a method of content-based image retrieval using object region in order to overcome disadvantages of existing color histogram methods. The existing color histogram methods have a weak point of reducing accuracy, because these have both a quantization error and an absence of spatial information. In order to overcome this problem, we convert a color information to a HSV space, quantize hue factor being pure color information, and calculate histogram. And then we use hue for retrieval feature that is robust in brightness, movement, and rotation. To solve the problem of the absence of spatial information, we select object region in terms of color feature and region correlation. And we use both the edge and the DC in the selected region for retrieving. As a result of experiment with 1,000 natural color images, the proposed method shows better precision and recall than the existing methods.

• Journal of Advanced Navigation Technology
• /
• v.16 no.2
• /
• pp.394-400
• /
• 2012

SURF is a robust local invariant feature descriptor and has been used in many applications such as object recognition. Even though this algorithm has similar matching accuracy compared to the SIFT, which is another popular feature extraction algorithm, it has advantage in matching time. However, these descriptors do not consider relative location information of extracted interesting points to guarantee rotation invariance. Also, since they use gray image of original color image, they do not use the color information of images, either. In this paper, we propose a method for improving matching performance of SURF descriptor using the color and relative location information of interest points. The location information is built from the angles between the line connecting the centers of interest points and the orientation line constructed for the center of each interest points. For the color information, color histogram is constructed for the region of each interest point. We show the performance of our scheme through experiments.