• IEIE Transactions on Smart Processing and Computing
• /
• v.1 no.3
• /
• pp.125-132
• /
• 2012

This paper proposes an automatic object segmentation and background composition method for video communication over consumer mobile phones. The object regions were extracted based on the motion and color variance of the first two frames. To combine the motion and variance information, the Euclidean distance between the motion boundary pixel and the neighboring color variance edge pixels was calculated, and the nearest edge pixel was labeled to the object boundary. The labeling results were refined using the morphology for a more accurate and natural-looking boundary. The grow-cut segmentation algorithm begins in the expanded label map, where the inner and outer boundary belongs to the foreground and background, respectively. The segmented object region and a new background image stored a priori in the mobile phone was then composed. In the background composition process, the background motion was measured using the optical-flow, and the final result was synthesized by accurately locating the object region according to the motion information. This study can be considered an extended, improved version of the existing background composition algorithm by considering motion information in a video. The proposed segmentation algorithm reduces the computational complexity significantly by choosing the minimum resolution at each segmentation step. The experimental results showed that the proposed algorithm can generate a fast, accurate and natural-looking background composition.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.23 no.1
• /
• pp.78-89
• /
• 1999

Clothes enhance visual images through the interaction between space and background of the wearer. The influence of background is important as that of the clothes when the observer understands the images. We look at fashion pictures used as important as that various backgrounds are presented depending on the image of the clothes. The clothing the model wears in the pictures takes on shape and space which supports the clothes. The background interact to from the whole image. The background has an important influence on the delivery of image for the clothes. However when the clothes are presented in the background there are some cases that all or parts of clothes can be shown. We must consider the composition ratio of the clothes and background which influences the whole image of the clothing. These interactions and influences on the whole image in regards to clothing background and the ratio will be the focus of this study. clothing was Modern Mannish Casual, Feminine, Ground was decided artificial setting 1 natural setting 1, indoor setting 1, artificial setting 2, natural setting 2, indoor setting 2, Percentage of Clothing was 80% , 140%, 200%,. Thus visual stimulus were 72 pictures that were combined Clothing Ground and Percentage of Clothing, the main survey of questionary consisted of their evaluation of the Picture image combined Clothing and Ground by 30 semantic differential bi-polar scales and the subjects were 50 students majoring in clothing and textile. The data analyzed by factor analysis MCA, MDS, The major finding were as follows : 1) As a result of factor analysis, 5 factors -Attractiveness Hardness and softness Cuteness Attention Cool and Warm factor were found out as constructing factors the Picture image combined Clothing and Ground 2) According to multidimensional positioning map were presented in a stimulus position the perceptive image differed in degree of similarity as a ground construction of stimulus in spite of same clothing image. It will aid in choosing the most beneficial background for any clothing brand. It will enhance the picture images to their full potential in any advertising medium.

• Journal of Digital Contents Society
• /
• v.15 no.4
• /
• pp.449-455
• /
• 2014

Detection of moving objects is a fundamental task in most of the computer vision applications, such as video surveillance, activity recognition and human motion analysis. This is a difficult task due to many challenges in realistic scenarios which include irregular motion in background, illumination changes, objects cast shadows, changes in scene geometry and noise, etc. In this paper, we propose an foreground extraction algorithm based on codebook, a database of information about background pixel obtained from input image sequence. Initially, we suppose a first frame as a background image and calculate difference between next input image and it to detect moving objects. The resulting difference image may contain noises as well as pure moving objects. Second, we investigate a codebook with color and brightness of a foreground pixel in the difference image. If it is matched, it is decided as a fault detected pixel and deleted from foreground. Finally, a background image is updated to process next input frame iteratively. Some pixels are estimated by input image if they are detected as background pixels. The others are duplicated from the previous background image. We apply out algorithm to PETS2009 data and compare the results with those of GMM and standard codebook algorithms.

• Journal of the Korea Society of Computer and Information
• /
• v.10 no.2 s.34
• /
• pp.59-68
• /
• 2005

Object tracking in a real time image is one of interesting subjects in computer vision and many practical application fields Past couple of years. But sometimes existing systems cannot find object by recognize background noise as object. This paper proposes a method of object detection and tracking using adaptive background image in real time. To detect object which does not influenced by illumination and remove noise in background image, this system generates adaptive background image by real time background image updating. This system detects object using the difference between background image and input image from camera. After setting up MBR(minimum bounding rectangle) using the internal point of detected otject, the system tracks otiect through this MBR. In addition, this paper evaluates the test result about performance of proposed method as compared with existing tracking algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.7 no.6
• /
• pp.1243-1248
• /
• 2006

Object tracking in a real time image is one of interesting subjects in computer vision and many practical application fields past couple of years. But sometimes existing systems cannot find object by recognize background noise as object. This paper proposes a method of object detection and tracking using adaptive background image in real time. To detect object which does not influenced by illumination and remove noise in background image, this system generates adaptive background image by real time background image updating. This system detects object using the difference between background image and input image from camera. After setting up MBR(minimum bounding rectangle) using the internal point of detected object, the system tracks object through this MBR. In addition, this paper evaluates the test result about performance of proposed method as compared with existing tracking algorithm.

• Journal of Korea Multimedia Society
• /
• v.21 no.9
• /
• pp.1044-1051
• /
• 2018

In this paper, we propose a new method to improve low light image. In order to improve the image quality of a night image with a moving object as much as the quality of a daytime image, the following tasks were performed. Firstly, we reduce the noisy of the input night image and improve the night image by the tone mapping method. Secondly, we segment the input night image into a foreground with motion and a background without motion. The motion is detected using both the difference between the current frame and the previous frame and the difference between the current frame and the night background image. The background region of the night image takes pixels from corresponding positions in the daytime image. The foreground regions of the night image take the pixels from the corresponding positions of the image which is improved by the tone mapping method. Experimental results show that the proposed method can improve the visual quality more clearly than the existing methods.

• Proceedings of the IEEK Conference
• /
• 2003.11a
• /
• pp.39-42
• /
• 2003

In this paper, we propose a background segmentation method in low resolution color image. A segmentation algorithm is based on color and edge information. In edge image, adaptive and local thresholds are applied to suppress paint boundaries. Through our experiments, the proposed algorithm efficiently segments background from objects.

• International Journal of Aeronautical and Space Sciences
• /
• v.10 no.1
• /
• pp.83-90
• /
• 2009

A new IRF (Impulse Response Function) analysis technique in high resolution SAR image is presented by taking into account the real clutter environment. In order to investigate the realistic effect of clutter background on the impulse response function of SAR image, an ideally generated impulse response function is superimposed with a large number of background clutter data which are extracted from the various regions of an actual SAR image. As a performance measure, PSLR (Peak Sidelobe Ratio) of the clutter-contained IRF is presented in the various groups of clutter background, and finally the results are compared with the stochastic model.

• 한국HCI학회:학술대회논문집
• /
• 2009.02a
• /
• pp.631-636
• /
• 2009

Foreground segmentation methods have steadily been researched in the field of computer vision. Especially, background subtraction which extracts a foreground image from the difference between the current frame and a reference image, called as "background image" have been widely used for a variety of real-time applications because of low computation and high-quality. However, if the background scene was dynamically changed, the background subtraction causes lots of errors. In this paper, we propose an efficient background subtraction method in dynamic environment with both static and dynamic scene. The proposed method is a hybrid method that uses the conventional background subtraction for static scene and depth information for dynamic scene. Its validity and efficiency are verified by demonstration in dynamic environment, where a video projector projects various images in the background.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.6 s.44
• /
• pp.151-156
• /
• 2006

This paper presents an background edge generation based automatic algorithm for detection of moving objects under moving camera. Background image is generated by rotating the fixed the camera on the tripod horizontally, aligning and reorganizing this images. We develop an efficient approach for robust panoramic background edge generation as well as method of edge matching between input image and background image. We applied the proposed algorithm to real image sequences. The proposed method can be successfully realized in various monitoring systems like intrusion detection as well as video surveillance.