• Journal of Digital Contents Society
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• v.10 no.4
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• pp.569-578
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• 2009

In this paper, we describe the color reproduction system for color images captured by digital camera. The system uses a color compensation chart to estimate the transformation between the colors in the image and the reference colors in the chart. The color reproduction process consists of two steps, i.e., the profile creation process and the profile application process. During the pro-file creation process, the relationships between the captured colors and the ref-erence colors are estimated. And the system creates a color profile and embeds the estimation result in the profile. During the profile application process, the colors in the images which are captured under the same condition as that of the chart image are reproduced using the created color profile. To evaluate the per-formance of the system, we perform experiments under various conditions. And we compare the results with those of widely used commercial applications.

• Korean Institute of Interior Design Journal
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• v.24 no.5
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• pp.42-50
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• 2015

In the 21st century, university library is changing into a new paradigm. Among others, color image emerges as an important aspect of the library. Up to now, studies on colors of indoor space have been limited on partial and specific spaces. But, this study, using the tool of emotional evaluation, aims to do a comprehensive research on color image of the whole space. This research uses the H University library completed in March 2015. This research is performed in the following procedure. First, previous related researches for the past ten years from 2005 to 2015 is examined, which will help understand the trends in this kind of research, and set up the concrete goal of research. By literature review, color image is established in the environmental psychological aspect. Second, to analyze colors, all the spaces of the library from the entrance lobby are filmed. Filmed images are changed into mosaic, and color palettes are composed, and color values are calculated using the Munsell color system. Third, emotional words are extracted, and emotional evaluation is made. Using the Semantic Differential scale method, emotional differences among subjects are compared, and the validity of the survey data is tested using the statistical program SPSS 18.0. As the outcome of the research shows, the color image and emotion in space are closely related. And, through emotion, it is possible to get color image, and this aspect can be scholastically systemized and developed.

• Journal of KIISE:Databases
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• v.35 no.5
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• pp.379-390
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• 2008

Due to the increase of the amount of image data, the demand for searching similar images is continuously increasing. Therefore, many researches about the content-based image retrieval (CBIR) are conducted to search similar images effectively. In CBIR, it uses image contents such as color, shape, and texture for more effective retrieval. However, when we apply CBIR to satellite images which are complex and pose the difficulty in using color information, we can have trouble to get a good retrieval result. Since it is difficult to use color information of satellite images, we need image segmentation to use shape information by separating the shape of an object in a satellite image. However, because satellite images are complex, image segmentation is hard and poor image segmentation results in poor retrieval results. In this paper, we propose a new approach to search similar images without image segmentation for satellite images. To do a similarity search without image segmentation, we define a similarity of an image by considering SIFT keypoint descriptors which doesn't require image segmentation. Experimental results show that the proposed approach more effectively searches similar satellite images which are complex and pose the difficulty in using color information.

• Journal of the Semiconductor & Display Technology
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• v.18 no.2
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• pp.67-72
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• 2019

This paper proposes a new method for the recognition of resistor color band using a color segmentation in a HSI color model. The proposed method firstly segments a resistor in a chromatic color as a ROI from a background. Secondly, the color bands of the resistor are segmented by vertical projection profile using both the intensity and the saturation differentiation and finally, it recognizes the colors of the segmented color bands using hue, saturation and intensity values. The final results are the value of the resistor and the names of the recognized color. The proposed method is implemented using C language in Raspberry Pi system with a camera module for a real-time image processing. Experiments were conducted by using various resistor images. The results show that the proposed method is successful for the recognition of resistor color band.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.3
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• pp.95-101
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• 2006

A face detection plays an important role in face recognition, video surveillance, and human computer interaction. In this paper, we propose a progressive threshold method to detect human faces in real time. The consecutive face images are acquired from camera and transformed into YCbCr color space images. The skin color of the input images are separated using a skin color filter in the YCbCr color space and some candidated face areas are decided by connected component analysis. The intensity equalization is performed to avoid the effect of many circumstances and an arbitrary threshold value is applied to get binary images. The eye area can be detected because the area is clearly distinguished from others in the binary image progressive threshold method searches for an optimal eye area by progressively increasing threshold from low values. After progressive thresholding, the eye area is normalized and verified by back propagation algorithm to finalize the face detection.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.511-521
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• 2011

As the use of image input and output devices increases, the importance of extracting text area in color images is also increasing. In this paper, in order to extract text area of the images efficiently, we present a text area extraction method for color images based on labeling and gradient difference method. The proposed method first eliminates non-text area using the processes of labeling and filtering. After generating the candidates of text area by using the property that is high gradient difference in text area, text area is extracted using the post-processing of noise removal and text area merging. The benefits of the proposed method are its simplicity and high accuracy that is better than the conventional methods. Experimental results show that precision, recall and inverse ratio of non-text extraction (IRNTE) of the proposed method are 99.59%, 98.65% and 82.30%, respectively.

• Journal of the Korean Graphic Arts Communication Society
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• v.27 no.1
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• pp.1-14
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• 2009

The color reproduction of digital still camera does not, in general, match those of the final output device. Because color gamut of these devices is different, it is therefore necessary to take account of a way to match. The way uses the optimized profile to output device an image. This paper proposed a way to create the input profile of digital still camera for standardization soft proofing process. The results of proposed way showed that for input profiles equivalent, good results relatively. In this paper, an experiment was done where the illumination sources used as the standard illumination 5200K and illuminated at a $45^{\circ}$ angle in the best illumination efficiently. The white balance was in mode 'custom' : aperture F11, exposure time 1/60s, ISO50, focal length 80mm. The images were exported and saved as 16bit RGB TIFF(AdobeRGB, sRGB, ProphotoRGB) images. To do the test, the RGB values of the RGB TIFF images are processed through the ICC input profile to arrive at processed $CIEL^*a^*b^*$ values. A profiling tool such as ProfileMaker 5.0 and Monacoprofile 4.8 are used to do this. The processed $CIEL^*a^*b^*$ values are compared to the reference $CIEL^*a^*b^*$ values and these two values are used to calculate a ${\Delta}E{^*}_{ab}$.

• Journal of the Korea Computer Graphics Society
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• v.24 no.1
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• pp.27-33
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• 2018

This paper presents a new adaptive LSB steganography for high capacity in spatial color images. The number of least signi ficant bit (LSB) of each RGB component in a color image pixel, to replace with the data bits to be hidden, was determine d through analysis of the worst case peak signal noise ratio (PSNR). In addition, the combination of the number of bits is determined adaptively according to image content. That is, 70% of the data to be hidden is proposed to be replaced with 3 bit LSB of two components, 2 bit LSB of the rest component, and 30% be replaced with 4 bit LSB of each RGB compon ent. To find edge areas in an image, delta sorting in local area is also suggested. Using the proposed method, the data cap acity is 9.2 bits per pixel (bpp). The average PSNR value of the tested images with concealed data of up to 60Kbyte was 43.9 db and also natural histograms were generated.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.2
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• pp.266-279
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• 2010

This research investigates the influence of color as an important factor of the visual image created by clothes. First, the factor analysis of the adjectives describing the images of clothes shows that the images of clothes are classified into 4 factors that include attraction, brightness, femininity, and the figure type (of which the attraction factor and brightness factor were found to be important dimensions). Second, as for the images of feminine style clothes colors, violet appears more refined and attractive than other colors in all 3 tones. Red appears as a brilliant and glowing image in a vivid tone. Yellow in a vivid tone and pale tone, and red in deep tone appear as a warm image, while blue appears as a cold image in all 3 tones. Blue and violet appear as a tall and slim image in all 3 tones. As for the images of mannish style clothes colors, yellow in vivid tone, violet in pale tone and red in deep tone appear as the most refined and attractive image, while green in all the tones appears as a rustic and unattractive image. Red in vivid tone, yellow in pale tone and violet in deep tone appear as a very brilliant and glowing image. Red in pale tone and deep tone appear as a warm and feminine image. Third, yellow in all the tones is evaluated to be attractive in the mannish style in the comparison of the image of feminine and mannish style clothes color, while blue in a pale tone in feminine style and in deep tone in mannish style earned high points. Red and violet did not show any significant differences between the two styles.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.737-744
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• 2005

In this paper, we propose a three-level color clustering algerian for the binarization of text regions extracted from natural scene images. The proposed algorithm consists of three phases of color segmentation. First, the ordinary images in which the texts are well separated from the background, are binarized. Then, in the second phase, the input image is passed through a high pass filter to deal with those affected by natural or artificial light. Finally, the image Is passed through a low pass filter to deal with the texture in texts and/or background. We have shown that the proposed algorithm is more effective used gray-information binarization algorithm. To evaluate the effectiveness of the proposed algorithm we use a commercial OCR software ARMI 6.0 to observe the recognition accuracies on the binarized images. The experimental results on word and character recognition show that the proposed approach is more accurate than conventional methods by over $35\%$.