• The KIPS Transactions:PartB
• /
• v.14B no.4
• /
• pp.255-262
• /
• 2007

This paper proposes an enhanced skin color-based detection method to find a region of human face in color images. The proposed detection method combines three color spaces, RGB, $YC_bC_r$, YIQ and builds color union histograms of luminance and chrominance components respectively. Combined color union histograms are then fed in to the back-propagation neural network for training and Levenberg-Marquadt algorithm is applied to the iteration process of training. Proposed method with Levenberg-Marquadt algorithm applied to training process of neural network contributes to solve a local minimum problem of back-propagation neural network, one of common methods of training for face detection, and lead to make lower a detection error rate. Further, proposed color-based detection method using combined color union histograms which give emphasis to chrominance components divided from luminance components inputs more confident values at the neural network and shows higher detection accuracy in comparison to the histogram of single color space. The experiments show that these approaches perform a good capability for face region detection, and these are robust to illumination conditions.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.39 no.2
• /
• pp.69-78
• /
• 2002

This paper addresses a method to automatically detect out a person's face from a given image that consists of a hair and face view of the person and a complex background scene. Out method involves an effective detection algorithm that exploits the spatial distribution characteristics of human skin color via an adaptive fuzzy color classifier (AFCC), The universal skin-color map is derived on the chrominance component of human skin color in Cb, Cr and their corresponding luminance. The desired fuzzy system is applied to decide the skin color regions and those that are not. We use RGB model for extracting the hair color regions because the hair regions often show low brightness and chromaticity estimation of low brightness color is not stable. After some preprocessing, we apply convex-hull to each region. Consequent face detection is made from the relationship between a face's convex-hull and a head's convex-hull. The algorithm using the convex-hull shows better performance than the algorithm using pattern method. The performance of the proposed algorithm is shown by experiment. Experimental results show that the proposed algorithm successfully and efficiently detects the faces without constrained input conditions in color images.

• Proceedings of the Korea Contents Association Conference
• /
• 2008.05a
• /
• pp.187-190
• /
• 2008

China has had a long preference in red. The color, symbolizing the sun, has a special significance, which stems from ancient times. The worship of the sun in the primitive society has been inherited by means of the collective unconsciousness; the sun has represented a variety of values such as nobility, purity, integrity, prosperity, success, happiness, good fortune, auspiciousness, and still much more. This research studies how the Chinese artworks visualize the color 'red', emphasizing the image of China and her culture. To do this, "Red Color" in Chinese posters from the past to the present were analyzed. While the images in red were delivered with a strong political connotation in the middle of the 20th century, as time passes by, the world trend of globalization has led the recent poster design in China to present red as the color standing for Chinese tradition, culture and spirits, which have flown throughout the 5000-year-long history.

• Journal of Broadcast Engineering
• /
• v.23 no.1
• /
• pp.146-153
• /
• 2018

This paper presents a superresolution demosaicing technique that can restore high-resolution color image from differently blurred low resolution images in Bayer domain. The proposed superresolution demosaicing algorithm uses an aperture mask wheel to get differently blurred low resolution images, so we just need to estimate point spread function at each frame. In addition, it does not require image registration because there is no translational motion between low resolution images. By using a rotatable aperture mask wheel, consecutive captured images provide sufficiently exclusive information for superresolution. Therefore, the proposed method can reduce the registration error between the low-resolution image as well as the calculation amount for superresolution restoration. The existing lens system of the camera can be extended to obtain a superresolution image by only adding an rotatable aperture mask wheels. Finally, in order to verify the performance of the proposed system, experimental results are performed. The proposed method showed the significant improvements in the sense of spatial and color resolution.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.11
• /
• pp.2271-2283
• /
• 2015

In this paper, we propose a method which infers an accurate disparity map for radiometrically varying stereo images. For this end, firstly, we transform the input color images to the log-chromaticity color space from which a linear relationship can be established during constructing a joint pdf between input stereo images. Based on this linear property, we present a new stereo matching cost by combining weighted mutual information and the SIFT (Scale Invariant Feature Transform) descriptor with segment-based plane-fitting constraints to robustly find correspondences for stereo image pairs which undergo radiometric variations. Experimental results show that our method outperforms previous methods and produces accurate disparity maps even for stereo images with severe radiometric differences.

• Journal of Broadcast Engineering
• /
• v.18 no.3
• /
• pp.393-400
• /
• 2013

Hand shape recognition is a fundamental technique for implementing natural human-computer interaction. In this paper, we discuss a method for effectively detecting a hand region in Kinect-based hand shape recognition. Since Kinect is a camera that can capture color images and infrared images (or depth images) together, both images can be exploited for the process of detecting a hand region. That is, a hand region can be detected by finding pixels having skin colors or by finding pixels having a specific depth. Therefore, after analyzing the performance of each, we need a method of properly combining both to clearly extract the silhouette of hand region. This is because the hand shape recognition rate depends on the fineness of detected silhouette. Finally, through comparison of hand shape recognition rates resulted from different hand region detection methods in general environments, we propose a high-performance hand region detection method.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39A no.8
• /
• pp.453-458
• /
• 2014

In this paper, we propose a stereo image composition method based on Poisson image editing. If we synthesize images without considering their depth values, it may lead to unwanted consequences. When we segment an image into its background and foreground regions using Grabcut, we take into account their geometric positions to mix color tones; thus, the image is composited more naturally. After synthesizing images, we apply a blurring operation around object boundaries; then, the foreground object and background are composited more seamlessly. In addition, we can adjust the distance of the object by setting arbitrary depth values and generating right color and depth images automatically. Experimental results show that the proposed stereo image composition method provides naturally synthesized stereo images. Improved portions were subjectively confirmed as well.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.4
• /
• pp.45-50
• /
• 2004

In this paper, we propose a new PCA-based LDA Mixture Algorithm(PLMA) for real-time face recognition system. This system greatly consists of the two parts: 1) face extraction part; 2) face recognition part. In the face extraction part we applied subtraction image, color filtering, eyes and mouth region detection, and normalization method, and in the face recognition part we used the method mixing PCA and LDA in extracted face candidate region images. The existing recognition system using only PCA showed low recognition rates, and it is hard in the recognition system using only LDA to apply LDA to the input images as it is when the number of image pixels ire small as compared with the training set. To overcome these shortcomings, we reduced dimension as we apply PCA to the normalized images, and apply LDA to the compressed images, therefore it is possible for us to do real-time recognition, and we are also capable of improving recognition rates. We have experimented using self-organized DAUface database to evaluate the performance of the proposed system. The experimental results show that the proposed method outperform PCA, LDA and ICA method within the framework of recognition accuracy.

• The Journal of the Korea Contents Association
• /
• v.11 no.1
• /
• pp.113-122
• /
• 2011

Visual images are very close to our living and we make decisions and choose behavioral options with the visual images on mass media. In current-affair documentary programs, interviews have potential effects that can change public opinions on important issues. Therefore, it's a consequence that the study examined how different expressions of visual images in documentary. Using preceding research methods, this study focus on form, color, movement and depth of visual images. This study analyzed quantitatively all interview shots with 15 current-affair documentary programs from major TV stations such as KBS, MBC and SBS. The findings of the study are 1) half of interview shots used the visual image expressions to hide interviewees' face according to the shield law, 2) choosing close-up shots in company with bust shots, 3) using natural lights and hand-held camera techniques for interviews, and 4) showing wide angles without depths of visual image.

• Korean Institute of Interior Design Journal
• /
• v.22 no.5
• /
• pp.171-178
• /
• 2013

In this study, we sought to find out the effect of different emotional interior images of the community facilities in an apartment complex on a youth brain wave by analyzing an Electroencephalograph (EEG). Based on the frequency of usage, we selected learning facilities, cultural facilities, and sport facilities. For brain stimulation, the visual stimulants with three different emotional words, cheerful, gentle, and elegant, were used based on I.R.I image scale. Overall, total nine different emotional images were used. Based on our findings, we conclude that: first, in order to improve learning concentration of the youth, a learning facility for the youth needs to be designed by skillfully combining the soft and comfortable colors from the gentle image and the murky and dark colors from the elegant image. Second, when designing a cultural facility, it is preferable to consider the elegant image for a calm and comfortable space. Third, a sport facility design needs to preclude dark colors and apply light colors to create a dynamic and lively space. Furthermore, we found out that the youth has established static images of each functionally different facility through their experience and learning. Therefore, it is imperative to plan community facilities in an apartment complex in a way to connect the space function with the emotional characteristics of the youth in order to support and encourage energetic activities and learning of the community youth.