• Journal of Information Processing Systems
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• v.7 no.3
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• pp.519-530
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• 2011

A Snake is an active contour for representing object contours. Traditional snake algorithms are often used to represent the contour of a single object. However, if there is more than one object in the image, the snake model must be adaptive to determine the corresponding contour of each object. Also, the previous initialized snake contours risk getting the wrong results when tracking multiple objects in successive frames due to the weak topology changes. To overcome this problem, in this paper, we present a new snake method for efficiently tracking contours of multiple objects. Our proposed algorithm can provide a straightforward approach for snake contour rapid splitting and connection, which usually cannot be gracefully handled by traditional snakes. Experimental results of various test sequence images with multiple objects have shown good performance, which proves that the proposed method is both effective and accurate.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.223-230
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• 2001

This paper proposes a new contour detection method and adaptive reconstruction scheme for the cylindrical organs, such as blood vessels or arteries. Furthermore, we present java-based navigation controller which has been built to examine the inside of cylindrical objects. Tn the preprocessing procedure, a few preprocessing image filters are applied in order to remove unwanted artifacts from the medical images and to estimate threshold values for the object of interest. We define a context-free grammar, which is proper fur properties of contours of cylindrical objects. In the next procedure, we extract contours using advanced radial gradient method and represent contours as context-free grammar derivation trees. We build polygons between two contours efficiently by traversing the derivations trees of the contours. We fly through the reconstructed virtual models using java-based navigation controller and VRML viewer.

• Proceedings of the KSRS Conference
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• v.2
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• pp.610-614
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• 2006

In this paper the advanced method of geodesic active contours was developed for the task of building detection from aerial and satellite images. Automatic extraction of man-made structures including buildings, building blocks or roads from remote sensing data is useful for land use mapping, scene understanding, robotic navigation, image retrieval, surveillance, emergency management procedures, cadastral etc. A level set method based on a region-driven segmentation model was implemented with which building boundaries were detected, through this curve propagation technique. The essence of this approach is to optimize the position and the geometric form of the curve by measuring information along that curve, and within the regions that compose the image partition. To this end, one can consider uniform intensities inside objects and the background. Thus, given an initial position of the curve, one can determine global, region-driven functions and provide a statistical description of the inside and outside object area. The calculus of variations and a gradient descent method was used to optimize the variational functional by an iterative steady state process. Experimental results demonstrate the potential of the proposed processing scheme.

• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.375-380
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• 2010

Most of previous algorithms of object boundary extraction have been studied for extracting the boundary of single object. However, multiple objects are much common in the real image. The proposed algorithm of extracting the boundary of each of multiple objects has two steps. In the first step, we propose the fast method using the outer and inner products; the initial contour including multiple objects is split and connected and each of new contours includes only one object. In the second step, an improved active contour model is studied to extract the boundary of each object included each of contours. Experimental results with various test images have shown that our algorithm produces much better results than the previous algorithms.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.925-926
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• 2008

This paper presents an object tracking method using motion vectors generated in the MPEG4 encoding process and the snake algorithm for active contours. This paper shows the possibility of realtime object tracking during MPEG4 encoding process in a conventional surveillance system. The experiments is performed on a PC platform to prove the effectiveness of the method.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.144-146
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• 2004

Stereo image analysis has been an important tool for reconstructing 3D terrain. By In its nature, occlusion is one of difficulties we cannot avoid in stereo matching. This paper presents a study on occlusion detection by employing LRC(Left-Right Check) and OCC(Occlusion Constraint). Experimental results show that these method can effectively detect occluded regions and those regions are usually occurred around object contours and scene discontinuity.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.321-329
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• 1999

Moving Object segmentation extracts an interested moving object on a consecutive image frames, and has been used for factory automation, autonomous navigation, video surveillance, and VOP(Video Object Plane) detection in a MPEG-4 method. This paper proposes new segmentation method using difference images are calculated with three consecutive input image frames, and used to calculate both coarse object area(AI) and it's movement area(OI). An AI is extracted by removing background using background area projection(BAP). Missing parts in the AI is recovered with help of the OI. Boundary information of the OI confines missing parts of the object and gives inital curves for active contour optimization. The optimized contours in addition to the AI make the boundaries of the moving object. Experimental results of a fast moving object on a complex background scene are included.

• International Journal of CAD/CAM
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• v.4 no.1
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• pp.33-45
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• 2004

In this work, a rational procedure has been formulated for the selection of points approximating slice contours cut in LOM (Laminated Object manufacturing) with first order approximation. It is suggested that the number of points representing a slice contour can be 'minimised' or 'optmised' by equating the horizontal chordal deviation (HCD) to the user-defined surface form tolerance. It has been shown that such optimization leads to substantial reduction in slice height calculations and NC codes file size for cutting out the slices. Due to optimization, the number of contour points varies from layer to layer, so that points on successive layer contours have to be matched by four sided ruled surface patches and triangular patches. The technological problems associated with the cutting out of triangular patches have been addressed. A robust algorithm has been developed for the determination of slice height for optimum and arbitrary numbers of contour points with different strategies for error calculations. It has been shown that optimisation may even lead to detection and appropriate representation of elusive surface features. An index of optimisation has been defined and calculations of the same have been tabulated.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.9-18
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• 2020

In the field of image processing, a method of detecting and counting passengers as moving objects when getting on and off the bus has been studied. Among these technologies, one of the artificial intelligence techniques, the deep learning technique is used. As another method, a method of detecting an object using a stereo vision camera is also used. However, these techniques require expensive hardware equipment because of the computational complexity of used to detect objects. However, most video equipments have a significant decrease in computational processing power, and thus, in order to detect passengers on the bus, there is a need for an image processing technology suitable for various equipment using a relatively low computational technique. Therefore, in this paper, we propose a technique that can efficiently obtain the number of passengers on the bus by detecting the contour of the object through the background subtraction suitable for low-cost equipment. Experiments have shown that passengers were counted with approximately 70% accuracy on lower-end machines than those equipped with stereo vision camera.

• Korean Journal of Cognitive Science
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• v.27 no.3
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• pp.355-376
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• 2016

We used holes defined by color similarity (Experiment 1) and binocular disparity (Experiment 2) to study how the inner contour of an object (i.e., boundary of a hole in it) is encoded in visual working memory. Many studies in VWM have shown that an object's boundary properties can be integrated with its surface properties via their shared spatial location, yielding an object-based encoding benefit. However, encoding of the hole contours has rarely been tested. We presented objects (squares or circles) containing a bar under a change detection paradigm, and relevant features to be remembered were the color of objects and the orientation of bars (or holes). If the contour of a hole belongs to the surrounding object rather than to the hole itself, the object-based feature binding hypothesis predicts that the shape of it can be integrated with color of an outer object, via their shared spatial location. Thus, in the hole display, change detection performance was expected to better than in the conjunction display where orientation and color features to be remembered were assigned to different parts of a conjunction object, and comparable to that in a single bar display where both orientation and color were assigned into a single bar. However, the results revealed that performance in the hole display did not differ from that in the conjunction display. This suggests that the shape of holes is not automatically encoded together with the surface properties of the outer object via object-based feature binding, but encoded independently from the surrounding object.