• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.3
• /
• pp.202-208
• /
• 2013

In the image processing for VS (Video Surveillance), the detection of moving entities in a monitored scene is an important step. A background subtraction technique has been widely employed to find the moving entities. However, the extracted foreground regions often include not only real entities but also their cast shadows, and this can cause errors in following image processing steps, such as tracking, recognition, and analysis. In this paper, a novel technique is proposed to determine the shadow pixels of moving objects in the foreground image of a VS camera. Compared to existing techniques where the same decision criteria are applied to all moving pixels, the proposed technique determines shadow pixels using local features based on two facts: First, the amount of pixel intensity drop due to a shadow depends on the intensity level of background. Second, the distribution pattern of pixel intensities remains even if a shadow is cast. The proposed method has been tested at various situations with different backgrounds and moving humans in different colors.

• Journal of Broadcast Engineering
• /
• v.20 no.5
• /
• pp.718-727
• /
• 2015

In this paper, we present a novel segmentation method that can extract new foreground objects from a current frame in real-time. It is performed by detecting differences between the current frame and reference frame taken from a fixed camera. We minimize computing complexity for real-time video processing. First DCT (Discrete Cosine Transform) is utilized to generate rough binary segmentation maps where foreground and background regions are separated. DCT shows better result of texture analysis than previous methods where texture analysis is performed in spatial domain. It is because texture analysis in frequency domain is easier than that in special domain and intensity and texture in DCT are taken into account at the same time. We maximize run-time efficiency of DCT by considering color information to analyze object region prior to DCT process. Last we use Guided filter for natural matting of the generated binary segmentation map. In general, Guided filter can enhance quality of intermediate result by incorporating guidance information. However, it shows some limitations in homogeneous area. Therefore, we present an additional method which can overcome them.

• Agricultural and Biosystems Engineering
• /
• v.3 no.1
• /
• pp.35-43
• /
• 2002

The spectral color resolution of an image is very important in color image analysis. Two factors influencing the spectral color resolution of an image are illumination intensity and lens aperture for a selected vision system. An optimal combination of illumination intensity and lens aperture for color image analysis was determined in the study. The method was based on a model of dynamic range defined as the absolute difference between digital values of selected foreground and background color in the image. The role of illumination intensity in machine vision was also described and a computer program for simulating the optimal combination of two factors was implemented for verifying the related algorithm. It was possible to estimate the non-saturating range of the illumination intensity (input voltage in the study) and the lens aperture by using a model of dynamic range. The method provided an optimal combination of the illumination intensity and the lens aperture, maximizing the color resolution between colors of interest in color analysis, and the estimated color resolution at the combination for a given vision system configuration.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.6
• /
• pp.537-641
• /
• 2007

In this paper, motion analysis algorithm is presented for home surveillance of the aged who lives alone. For the first step, we acquire images from a camera. To enhance the image, we use median filtering and binarize it to reduce processing time. And then morphological operations are performed to remove small blobs and small holes. At the forth step, blobs are analysed to extracts tor foreground region. Then, motions are predicted from these images by using optical tlow technique, and the predicted motion data are refined by comparing our cardboard models so as to judge behavior pattern.

• International Journal of Advanced Culture Technology
• /
• v.4 no.4
• /
• pp.45-50
• /
• 2016

This is a humanistic study to trace phenomena logically the comprehensive therapeutic mechanism of the human body which is coded by the smart emotion of the rated signal conveyed by the Rated Sijo. The Gestalt, which is structured in the form of therapeutic metastasis conveyed by sentences, is intended to embody the principle of human response. So, this researcher explored the metastatic structure toward Gestalt of original human being through the passage of foreground and background by ergonomic and chemical structure. In the meantime, this researcher focused on revealing the structure of the field of existence by the symbol system in which the therapeutic mechanism of the human body is embodied. As a result, the basic framework of Gestalt literary therapy, which contributes to the improvement of the Quality of Life metaphorized as a mechanism of the symbol system by the metastasis of literary therapy or the electrical operation of the human body. As a result, the human body as a conductor through literature has turned out to be an original Gestalt structure pursued by literature. In addition, it was analyzed that the human body would accept signals such as emotions and Rated Emotions planted in the sentence, and synapse them into the human physiological psycho analytical symbol system. Therefore, it has been confirmed possibility that human existent environment and trauma are separated from the whole universe can push fully implement therapeutic techniques toward totalization by a combination of literary devices, especially appropriate electric signal combination of the Rated Sijo.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.6
• /
• pp.741-747
• /
• 2012

In this paper, we propose a fast and robust framework for detecting and tracking multiple targets. The proposed system includes two modules: object detection module and object tracking module. In the detection module, we preprocess the input images frame by frame, such as gray and binarization. Next after extracting the foreground object from the input images, morphology technology is used to reduce noises in foreground images. We also use a block-based histogram analysis method to distinguish human and other objects. In the tracking module, color-based tracking algorithm and Kalman filter are used. After converting the RGB images into HSV images, the color-based tracking algorithm to track the multiple targets is used. Also, Kalman filter is proposed to track the object and to judge the occlusion of different objects. Finally, we show the effectiveness and the applicability of the proposed method through experiments.

• Proceedings of the KIEE Conference
• /
• 2007.04a
• /
• pp.389-391
• /
• 2007

This paper describes about the printed character segmentation and recognition system for slabs in steel manufacturing process. To increase the recognition rate, it is important to improve success rate of character segmentation. Since Slabs front area surface are not uniform and surface temperature is very high, marked characters not only undergo damages but also have much noise. On the other hand, since almost marked characters are very thick and the space between characters is only about 10 $^{\sim}$ 15 mm, there are many touching characters. Therefore appropriate character image preprocessing and segmentation algorithm is needed. In this paper we propose a multi-local thresholding method for damaged character restoration, a modified touching character segmentation, algorithm for marked characters. Finally a effective Multi-Class SVM is used to recognize segmented characters.

• Annual Conference of KIPS
• /
• 2022.05a
• /
• pp.213-216
• /
• 2022

There has been an increase in video surveillance for public safety and security, which increases the video data, leading to analysis, and storage issues. Furthermore, most surveillance videos contain an empty frame of hours of video footage; thus, extracting useful information is crucial. The prominent framework used in surveillance for efficient storage and analysis is video synopsis. However, the existing video synopsis procedure is not applicable for creating an abnormal object-based synopsis. Therefore, we proposed a lightweight synopsis methodology that initially detects and extracts abnormal foreground objects and their respective backgrounds, which is stitched to construct a synopsis.

• Journal of Korea Spatial Information System Society
• /
• v.11 no.2
• /
• pp.45-53
• /
• 2009

The fast progress on multimedia data acquisition technologies has enabled collecting vast amount of videos in real time. Although the amount of information gathered from these videos could be high in terms of quantity and quality, the use of the collected data is very limited typically by human-centric monitoring systems. In this paper, we propose a framework for analyzing long traffic video using series of content-based analyses tools. Our framework suggests a method to integrate theses analyses tools to extract highly informative features specific to a traffic video analysis. Our analytical framework provides (1) re-sampling tools for efficient and precise analysis, (2) foreground extraction methods for unbiased traffic flow analysis, (3) frame property analyses tools using variety of frame characteristics including brightness, entropy, Harris corners, and variance of traffic flow, and (4) a visualization tool that summarizes the entire video sequence and automatically highlight a collection of frames based on some metrics defined by semi-automated or fully automated techniques. Based on the proposed framework, we developed an automated traffic flow analysis system, and in our experiments, we show results from two example traffic videos taken from different monitoring angles.

• Journal of The Korean Astronomical Society
• /
• v.43 no.1
• /
• pp.1-8
• /
• 2010

JHK near-infrared photometry of star clusters in the dwarf irregular/dwarf starburst galaxy NGC 1569 are presented. After adopting several criteria to exclude other sources (foreground stars, background galaxies, etc.), 154 candidates of star clusters are identified in the near-infrared images of NGC 1569, which include very young star clusters. Especially, from analysis based on theoretical background, we found ten very young star clusters near the center of NGC 1569. The total reddening values toward these clusters are estimated to be $A_V$=1-9 mag from comparison with the theoretical estimates given by the Leitherer et al. (1999)'s star cluster model.