• 한국HCI학회:학술대회논문집
• /
• 2007.02a
• /
• pp.298-301
• /
• 2007

Computational speed plays key role in background subtraction and shadow detection, because those are only preprocessing steps of a moving object segmentation, tracking and activity recognition. A color intensity variation based approach fastly detect a moving object and extract shadow in a image sequences. The moving object is subtracted from background using meanmax, meanmin thresholds and shadow is detected by decrease limit and correspondence thresholds. The proposed approach relies on the ability to represent shadow cast impact by offline experiment dataset on sub grouped RGB color space.

• Journal of Satellite, Information and Communications
• /
• v.9 no.4
• /
• pp.77-81
• /
• 2014

This paper propose a method to detect moving object and locating in real time from video sequence. first the proposed method extract moving object by differencing two consecutive frames from the video sequence. If the interval between captured two frames is long, it cause to generate fake moving object as tail of the real moving object. secondly this paper proposed method to overcome this problem by using doppler effects and HSV color model. finally the object segmentation and locating is done by combining the result that obtained from steps above. The proposed method has 99.2% of detection rate in practical and also this method is comparatively speed than other similar methods those proposed in past. Since the complexity of the algorithm is directly affects to the speed of the system, the proposed method can be used as low complexity algorithm for real time moving object detection.

• International Journal of Control, Automation, and Systems
• /
• v.1 no.1
• /
• pp.119-126
• /
• 2003

The problem of tracking moving objects in a video stream is discussed in this pa-per. We discussed the popular technique of optical flow for moving object detection. Optical flow finds the velocity vectors at each pixel in the entire video scene. However, optical flow based methods require complex computations and are sensitive to noise. In this paper, we proposed a new method based on the Hough transform and on voting accumulation for improving the accuracy and reducing the computation time. Further, we applied the Boo-lean based edge detector for edge detection. Edge detection and segmentation are used to extract the moving objects in the image sequences and reduce the computation time of the CHT. The Boolean based edge detector provides accurate and very thin edges. The difference of the two edge maps with thin edges gives better localization of moving objects. The simulation results show that the proposed method improves the accuracy of finding the optical flow vectors and more accurately extracts moving objects' information. The process of edge detection and segmentation accurately find the location and areas of the real moving objects, and hence extracting moving information is very easy and accurate. The Combinatorial Hough Transform and voting accumulation based optical flow measures optical flow vectors accurately. The direction of moving objects is also accurately measured.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2006.04a
• /
• pp.177-180
• /
• 2006

In this paper we proposed a method of automatic point segmentation acquired by 2D laser scanner to recognize moving objects. Recently, Laser scanner is noticed as a new method in the field of close range 3D modeling. But the majority of the researches are pointed on precise 3D modeling of static objects using expensive 3D laser scanner. 2D laser scanner is relatively cheap and can obtain 2D coordinate information of moving object's surface or can be utilized as 3D laser scanner by rotating the system body. In these reasons, some researches are in progress, which are adopting 2D laser scanner to robot control systems or detection of objects moving along linear trajectory. In our study, we automatically segmented point data of 2D laser scanner thus we could recognize each of the object passing through a section.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.10
• /
• pp.2552-2562
• /
• 1996

In this paper, we propose a segmentation algorithm that can reliably separate moving objects from noisy background in the image sequance received from a camera at the fixed position. The proposed algorithm consists of three processes:generation of the difference image between the input image and the reference image, multilevel quantization of the difference image, and multistagemerging in the quantized image. The quantization process requantizes the difference image based on the multiple threshold values determined bythe histogram analysis. The merging starts from the seed region which created by using the highest threshold value and ends when termination conditions are met. the proposed method has been tested with various real imge sequances containing intruders. The test results show that the proposed algorithm can detect moving objects like intruders very effectively in the noisy environment.

• Proceedings of the Korean Information Science Society Conference
• /
• 2001.10b
• /
• pp.385-387
• /
• 2001

비디오 객체 분할은 MPEG-4와 같은 객체 기반 코딩 단계를 위한 중요한 구성 요소이다. 새로운 MPEG-4 비디오 표준은 움직임 객체의 모양 정보를 고려하여 높은 효율의 부호화 뿐만 아니라 움직임 객체에 대한 내용기반 기능의 부호화를 수행한다. 본 논문은 비디오 시퀀스에서 움직임 객체 분할을 위한 새로운 알고리즘과 VOP(Video Object Plane) 추출 방법을 소개한다. 본 알고리즘은 첫 번째 프레임을 기준영상으로 설정한 후 두 개의 연속된 프레임 사이의 차이 값으로부터 시작된다. 즉 차이영상을 추출한 후 차이영상에 Canny 에지를 적용하고 다음 프레임의 영상에 Canny 에지와 morphologic일 연산을 적용하여 정확한 움직임 객체 에지(Moving Object Edge)를 생성한다. 이후 생성된 에지를 이용하여 VOP를 추출한다. VOP 추출 단계에서 더욱 정확한 움직임 객체 에지를 얻기 위하여 morphological 연산을 수행하였다.

• Proceedings of the IEEK Conference
• /
• 2005.11a
• /
• pp.1129-1132
• /
• 2005

In this paper, we proposed real-time stereoscopic image conversion algorithm using object segmentation and motion parallax. The proposed algorithm separates objects using luminance of image, extracts moving object among objects of the image using motion parallax and generates depth map. Parallax process is done based on the depth map. The proposed method has been evaluated using visual test and APD(Absolute Parallx Difference) for comparing the stereoscopic image of the proposed method with that of MTD. The proposed method offers realistic stereoscopic conversion effect regardless of the direction and velocity of the 2-D image.

• The Journal of the Korea Contents Association
• /
• v.7 no.2
• /
• pp.40-50
• /
• 2007

In this paper, we propose an efficient method for detecting and tracking multiple moving objects based on morphological region merging from real-time video sequences. The proposed approach consists of adaptive threshold extraction, morphological region merging and detecting and tracking of objects. Firstly, input frame is separated into moving regions and static regions using the difference of images between two consecutive frames. Secondly, objects are segmented with a reference background image and adaptive threshold values, then, the segmentation result is refined by morphological region merge algorithm. Lastly, each object segmented in a previous step is assigned a consistent identification over time, based on its spatio-temporal information. The experimental results show that a proposed method is efficient and useful in terms of real-time multiple objects detecting and tracking.

• Journal of Broadcast Engineering
• /
• v.1 no.2
• /
• pp.165-175
• /
• 1996

In this paper, the image segmentation method based on the hierarchical pyramid image structure of reduced resolution versions of the image for solving the problems in the conventional methods is presented. This method is described the object detection and delineation by statistical approach. In the object detection method, IFSVR( Inverse-father-son variance ratio) method and FSVR(father-son variance ratio ) method are proposed for solving clustering validity problem occurred In the hierarchical pyramid image structure. An optimal object pixel Is detected at some level by this method. In the object delineation method, the iterative algorithm by top-down traversing method is proposed for moving the optimal object pixel to levels of higher resolution. Using the computer simulation, the results by the proposed statistical methods and object traversing method are investigated for the binary Image and the real image. At the results of computer simulation, the proposed methods of image segmentation based on the hierarchical pyramid Image structure seem to have useful properties and deserve consideration as a possible alternative to existing methods of image segmentation. The computation for the proposed method is required 0(log n) for n${\times}$n input image.

• Journal of Broadcast Engineering
• /
• v.2 no.2
• /
• pp.146-155
• /
• 1997

The new video coding standard Iv1PEG-4 is enabling content-based functionalities. It requires a prior decomposition of sequences into video object planes (VOP's) so that each VOP represents moving objets. This paper addresses an image segmentation method for separating moving objects from still background (non-moving area) in video sequences using a statistical hypothesis test. In the proposed method. three consecutive image frames are exploited and a hypothesis testing is performed by comparing two means from two consecutive difference images. which results in a T-test. This hypothesis test yields a change detection mask that indicates moving areas (foreground) and non-moving areas (background), Moreover. an effective method for extracting