• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.213-217
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• 2008

This paper proposes a novel method for the recognition of passports based on the CDM(Conditional Dilation Morphology) masking and the ART2-based RBF neural networks. For the extraction of individual codes for recognizing, this paper targets code sequence blocks including individual codes by applying Sobel masking, horizontal smearing and a contour tracking algorithm on the passport image. Individual codes are recovered and extracted from the binarized areas by applying CDM masking and vertical smearing. This paper also proposes an ART2-based hybrid network that adapts the ART2 network for the middle layer. This network is applied to the recognition of individual codes. The experiment results showed that the proposed method has superior in performance in the recognition of passport.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.333-336
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• 2007

We propose a simple method for tracking a nonparameterized subject contour in a single video stream with a moving camera and changing background. Then we present a method to eliminate the tracked contour object by replacing with the background scene we get from other frame. Our method consists of two parts: first we track the object using LOD (Level-of-Detail) canny edge maps, then we generate background of each image frame and replace the tracked object in a scene by a background image from other frame that is not occluded by the tracked object. Our tracking method is based on level-of-detail (LOD) modified Canny edge maps and graph-based routing operations on the LOD maps. To reduce side-effects because of irrelevant edges, we start our basic tracking by using strong Canny edges generated from large image intensity gradients of an input image. We get more edge pixels along LOD hierarchy. LOD Canny edge pixels become nodes in routing, and LOD values of adjacent edge pixels determine routing costs between the nodes. We find the best route to follow Canny edge pixels favoring stronger Canny edge pixels. Our accurate tracking is based on reducing effects from irrelevant edges by selecting the stronger edge pixels, thereby relying on the current frame edge pixel as much as possible. This approach is based on computing camera motion. Our experimental results show that our method works nice for moderate camera movement with small object shape changes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.277-280
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• 2007

A moving object tracking algorithm for image searching based on specific color detection is proposed in this paper. That is preprocessed for a luminance variation and noise cancellation to be robust system. The motion tracking is used the difference between input image and reference image in R, G, B each channels for a moving image. The proposed method is enhanced to 15% fast in comparison with the contour tracking method and the matching method, and stable.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.10
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• pp.902-909
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• 2015

In this paper, monovision based relative navigation for a satellite proximity operation is studied. The chaser satellite only uses one camera sensor to observe the target satellite and conducts image tracking to obtain the target pose information. However, by using only mono-vision, it is hard to get the depth information which is related to the relative distance to the target. In order to resolve the well-known difficulty in computing the depth information with the use of a single camera, the active contour method is adopted for the image tracking process. The active contour method provides the size of target image, which can be utilized to indirectly calculate the relative distance between the chaser and the target. 3D virtual reality is used in order to model the space environment where two satellites make relative motion and produce the virtual camera images. The unscented Kalman filter is used for the chaser satellite to estimate the relative position of the target in the process of glideslope approaching. Closed-loop simulations are conducted to analyze the performance of the relative navigation with the active contour method.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.11-18
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• 2011

In the field of image processing to track the fingertip much research has been done. The most common way to calculate the fingertip first, to extract color information. Then, it uses Blob Coloring algorithms which are expressed in blob functions the skin contour and calculates. The algorithm from contour decides the highest location with the fingertip. But this method when measuring it location from the finger condition which bents is not the actual fingertip and has the problem which detects the location which goes wrong. This paper proposes the color space correction algorithm to tracks the fingertip which bents. The method which proposes when tracking the fingertip from the finger condition which bents solves the problem which measures the location which goes wrong. Aim of this paper in compliance with the propensity of the users forecasts a problem in advance and corrects with improvement at the time of height boil an efficiency. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the proposed method. Accordingly, the satisfaction and the quality of services will be improved the image recognition.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.243-248
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• 2011

In this paper, we propose a new method to extract palm lines and read it with simple techniques from one photo. We use morphological information and 8-directional contour tracking algorithm. From the digitalized image, we transform original RGB information to YCbCr color model which is less sensitive to the brightness information. The palm region is extracted by simple threshold as Y:65~255, Cb:25~255, Cr:130~255 of skin color. Noise removal process is then followed with morphological information of the palm such that the palm area has more than quarter of the pixels and the rate of width vs height is more than 2:1 and 8-directional contour tracking algorithm. Then, the stretching algorithm and Sobel mask are applied to extract edges. Another morphological information that the meaningful edges(palm lines) have between 10 and 20 pixels is used to exclude noise edges and boundary lines of the hand from block binarized image. Main palm lines are extracted then by labeling method. This algorithm is quite effective even reading the palm from a photographed by a mobile phone, which suggests that this method could be used in various applications.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.474-479
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• 2003

In this paper, we proposed the novel method for the recognition of English calling cards by using the projection method and the enhanced RBF (Radial Basis Function) network. The recognition of calling cards consists of the extraction phase of character areas and the recognition phase of extracted characters. In the extraction phase, first of all, noises are removed from the images of calling cards, and the feature areas including character strings are separated from the calling card images by using the horizontal smearing method and the 8-directional contour tracking method. And using the image projection method, the feature areas are split into the areas of individual characters. We also proposed the enhanced RBF network that organizes the middle layer effectively by using the enhanced ART1 neural network adjusting the vigilance threshold dynamically according to the homogeneity between patterns. In the recognition phase, the proposed neural network is applied to recognize individual characters. Our experiment result showed that the proposed recognition algorithm has higher success rate of recognition and faster learning time than the existing neural network based recognition.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.1
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• pp.32-39
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• 1997

One of the most important performance criteria in tuning the gain of position loop controller for CNC machining center is the contour error. In this papre we analyze contour error in the linear and circular interpolations for the axis-matched and mismatched cases. To have small contour errors, it is necessary to set the P gain for each axis to be same. And the D gain should be much smaller than the P gain. Baded on the analysis in the frequency domain, we propose a gain tuning method for the P and PD controllers. We show that the PD controller is better than the P controller. The effectiveness of this method is demonstrated by experiments.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.435-437
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• 1998

In this productive system, it needs to control the each axis motion harmoniously to perform accurately for the manufacturing, transporting and printing. Independent Axis Control usually used for this objection. However, if Independent Axis Control mismatched the parameter of each axis system or in the case of free curve tracking or the case of high speed control, there would be big contour error so that cannot achieve control objection. As a result, there is Contour Control method suggested to supply for this defect. This paper carried modeling of biaxial system and implemented Independent Axis Control & Contouring Control on straight line, circular, and coner path by simulation and experiment. If feedrate increased, contour error growed. In consequence, according to this factor, we introduced contouring controller, so we could find the fact that contour error was reduced more than that of independent axis control about each path.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.5
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• pp.39-46
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• 2007

Research on human identification in ubiquitous environment has recently attracted a lot of attention. As one of those research, gait recognition is an efficient method of human identification using physical features of a walking person at a distance. In this paper, we present a human shape extraction and tracking for gait recognition using geodesic active contour models(GACMs) combined with mean shift algorithm The active contour models (ACMs) are very effective to deal with the non-rigid object because of its elastic property. However, they have the limitation that their performance is mainly dependent on the initial curve. To overcome this problem, we combine the mean shift algorithm with the traditional GACMs. The main idea is very simple. Before evolving using level set method, the initial curve in each frame is re-localized near the human region and is resized enough to include the targe region. This mechanism allows for reducing the number of iterations and for handling the large object motion. The proposed system is composed of human region detection and human shape tracking modules. In the human region detection module, the silhouette of a walking person is extracted by background subtraction and morphologic operation. Then human shape are correctly obtained by the GACMs with mean shift algorithm. In experimental results, the proposed method show that it is extracted and tracked efficiently accurate shape for gait recognition.