• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.8 no.5
• /
• pp.1080-1088
• /
• 2004

In this paper, the interesting moving objects tracking algorithm using color information on Multi-Video camera against variance of intensity, shape and background is proposed. Moving objects are detected by using difference image method and integral projection method to background image and objects image only with hue area, after converting RGB color coordination of image which is input from multi-video camera into HSI color coordination. Hue information of the detected moving area are segmented to 24 levels from $0^{\circ}$ to $360^{\circ}$. It is used to the feature parameter of the moving objects that are three segmented hue levels with the highest distribution and difference among three segmented hue levels. To examine propriety of the proposed method, human images with variance of intensity and shape and human images with variance of intensity, shape and background are targeted for moving objects. As surveillance results of the interesting human, hue distribution level variation of the detected interesting human at each camera is under 2 level, and it is confirmed that the interesting human is tracked and surveilled by using feature parameters at cameras, automatically.

• Journal of Korea Multimedia Society
• /
• v.14 no.5
• /
• pp.607-613
• /
• 2011

In this paper, we propose a hand image segmentation method using the dynamic threshold values on input images with various lighting and background attributes. First, a moving hand silhouette is extracted using the camera input difference images, Next, based on the R,G,B histogram analysis of the extracted hand silhouette area, the threshold interval for each R, G, and B is calculated on run-time. Finally, the hand area is segmented using the thresholding and then a morphology operation, a connected component analysis and a flood-fill operation are performed for the noise removal. Experimental results on various input images showed that our hand segmentation method provides high level of accuracy and relatively fast stable results without the need of the fixed threshold values. Proposed methods can be used in the user interface of mixed reality applications.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.3
• /
• pp.594-601
• /
• 2009

Shooting simulation systems not only reduce a great amount of expense and time for military exercises but also prevent accidents. In particular, the shooting simulation systems using laser beam have an advantage which is very similar to the shooting exercise that uses real bullets. However, real time technique for laser beam recognition in a target image is necessary. The method proposed in this paper takes a difference image from two adjacent image frames. Then a thresholding is applied on this difference image to discriminate laser beam from background. To decide the threshold value the intensity distribution of background points is modeled assuming normal distribution. Then a noise reduction and a region segmentation are applied on the binary image to find the position of a laser beam. The time complexity of this process depends on the size of an image multiplied by the size of a mask used in the noise reduction process. The experimental result showed that the accuracy of the system was 93.3%. Even in the inaccurate cases the beam was always found in the resultant region.

• Proceedings of the IEEK Conference
• /
• 2008.06a
• /
• pp.1211-1212
• /
• 2008

In this paper, we propose image process modeling as a part of location based surveillance system for unauthorized target recognition and tracking in harbor, airport, military zone. For this, we compress and store background image in lower resolution and perform object extraction and motion tracking by using sobel edge detection and difference picture method between real images and a background image. In addition to, we use Independent Component Analysis Neural Network for moving target recognition. Experiments are performed for object extraction and tracking of moving targets on road by using static camera in 20m height building and it shows the robust results.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2009.10a
• /
• pp.1077-1080
• /
• 2009

In this paper, we propose a new method for measuring image sticking of an OLED display using a human visual test. We determined that the perceptual image sticking threshold is 2% of luminance difference at 200 nits and 1% at 100 nits, respectively. Color shift must also be considered when evaluating image sticking, as a ${\Delta}$(u', v') shift of just over 0.002 can be recognized regardless of background brightness. Perception of image sticking is affected by the background level, test pattern, and ambient illumination conditions. The evaluation standard must consider both luminance variation and color shift simultaneously.

• Journal of People, Plants, and Environment
• /
• v.22 no.1
• /
• pp.53-63
• /
• 2019

The purpose of this study was to investigate the preference of plant environmental images for flower plant consumption. This study came up with a total of four treatments including one image without plants and three images with flower plants (three roses, rose gift, rose garden). We conducted a survey on 104 men and women through the Google (online) survey and analyzed the data. The preference was higher with statistical significance for environmental images with plants than the image without plants. The preference for environmental images of roses was highest in the order of rose gift > rose garden > three roses. As a result of the cross-tabulation analysis, it was found that there was a significant difference in the preference for environmental images of roses according to general characteristics such as educational background and residence type. In terms of educational background, 2-year college graduates showed higher preference for the three environmental images of roses with statistical significance compared to high school graduates, university graduates and masters or higher. As a result of determining the difference in preference according to residential types, residents of multiplex houses showed higher preference for the "rose garden" environment image than residents of detached houses (p < .05). As a result of examining stress and depression in everyday life, 48.1% (the highest) of the respondents answered that they were "under daily stress" and 48.1% (the highest) of the respondents claimed not to be "under much depression". This study investigated the difference in preference according to demographic characteristics and existence of plants, preference in environmental images using roses, correlation with daily stress and depression, and utility of publicity using photographic images of plants.

• Journal of Korea Multimedia Society
• /
• v.6 no.3
• /
• pp.409-418
• /
• 2003

Object tracking in video is one of subject that computer vision and several practical application field have interest in several years. This paper proposes real time object tracking and face region extraction method that can be applied to security and supervisory system field. For this, in limited environment that camera is fixed and there is seldom change of background image, proposed method detects position of object and traces motion using difference between input image and background image. The system creates adaptive background image and extracts pixels in object using line scan method for more stable object extraction. The real time object tracking is possible through establishment of MBR(Minimum Bounding Rectangle) using extracted pixels. Also, effectiveness for security and supervisory system is improved due to extract face region in established MBR. And through an experiment, the system shows fast real time object tracking under limited environment.

• The Journal of the Korea Contents Association
• /
• v.11 no.5
• /
• pp.125-137
• /
• 2011

Recently the research on the system using images taken from camera phones as input is actively conducted. This paper proposed a system that shows wine pictures which are similar to the input wine label in order. For the calculation of the similarity of images, the representative color of each cell of the image, the recognized text color, background color and distribution of feature points are used as the features. In order to calculate the difference of the colors, RGB is converted into CIE-Lab and the feature points are extracted by using Harris Corner Detection Algorithm. The weights of representative color of each cell of image, text color and background color are applied. The image similarity is calculated by normalizing the difference of color similarity and distribution of feature points. After calculating the similarity between the input image and the images in the database, the images in Database are shown in the descent order of the similarity so that the effort of users to search for similar wine labels again from the searched result is reduced.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.63-66
• /
• 2009

Automatic segmentation of foreground from background in video sequences has attracted lots of attention in computer vision. This paper proposes a novel framework for the background subtraction that the foreground is segmented from the background by directly subtracting a background image from each frame. Most previous works focus on the extraction of more reliable seeds with threshold, because the errors are occurred by noise, weak color difference and so on. Our method has good segmentations from the approximate seeds by using the Random Walks with Restart (RWR). Experimental results with live videos demonstrate the relevance and accuracy of our algorithm.

• The KIPS Transactions:PartB
• /
• v.16B no.4
• /
• pp.271-280
• /
• 2009

In this paper, we propose a smoke detection method using region growing method in outdoor video sequences. Our proposed method is composed of three steps; the initial change area detection step, the boundary finding and expanding step, and the smoke classification step. In the first step, we use a background subtraction to detect changed areas in the current input frame against the background image. In difference images of the background subtraction, we calculate a binary image using a threshold value and apply morphology operations to the binary image to remove noises. In the second step, we find boundaries of the changed areas using labeling algorithm and expand the boundaries to their neighbors using the region growing algorithm. In the final step, ellipses of the boundaries are estimated using moments. We classify whether the boundary is smoke by using the temporal information.