• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.933-938
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• 1990

A method of recognizing 2-dimensional polygonal object is proposed by using a concept of generalized incremental circle transform. The generalized incremental circle transform, which maps boundaries of an object into a circular disc, represents efficiently the shape of the boundaries that are obtained from digirized binary images of the objects. It is proved that the generalized incremental circle transform of an object is invariant to object translation, rotation, and size, and can be used as feature information for recognizing two dimensional polygonal object efficiently.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.6
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• pp.861-870
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• 1990

A method of recognizing objects is proposed that uses a concept of modified incremental circle transform. The modified incremental circle transform, which maps bundaries of an object into an unit circle, represnets efficiently the shape of the boundaries detected in digitized binary images of the objects. It is proved that modified incremental circle transform of object, which is invariant under object translation, rotation, and size, can be used as feature information for recognizing two dimensional polygonal object efficiently.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.99.5-99
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• 2002

$\textbullet$ 3-D object tracking framework $\textbullet$ Using fast stereo vision system for range image $\textbullet$ Using CONDENSATION algorithm to tracking object $\textbullet$ For recognizing object, superquardrics model is used $\textbullet$ Our target object is like coils in steel works

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1546-1549
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• 2020

This paper introduces the development process of mobile home CCTV that enables remote control and object recognition using unused smartphones and Arduino. Clients can control motors connected to Arduino through button, enable bidirectional voice communication between client-server and receive video from the server in real time. The server sends a PUSH notification to the client when its battery is low. When the server recognizes the charger, the client's remote control allows the server to dock to the charger and charge it. It was confirmed that video and voice delivery between client and server works well without any problems, and that object recognition works smoothly.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.115-120
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• 2006

In This Paper, We Propose The Method To Reconstruct And Estimate Partially Occluded Elliptical Objects In Images From Overlapping And Cutting. We Present The Robust Method For Recognizing Partially Occluded Objects Based On Symmetry Properties, Which Is Based On The Contours Of Elliptical Objects. A Proposed Method Provides Simple Techniques To Reconstruct Occluded Regions Via A Region Copy Using The Symmetry Axis Within An Object. Based On The Estimated Parameters For Partially Occluded Objects, We Perform Object Recognition On The Classifier. Since A Proposed Method Relies On Reconstruction Of The Object Based On The Symmetry Properties Rather Than Statistical Estimates, It Has Proven To Be Remarkably Robust In Recognizing Partially Occluded Objects In The Presence Of Scale Changes, Object Pose, And Rotated Objects With Occlusion, Even Though h Proposed Method Has Minor Limitations Of Object Poses.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.5
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• pp.841-849
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• 2001

The pixel information of the object was obtained sequentially and pixels were clustered to a label by the line labeling method. Feature points were determined by finding the slope for edge pixels after selecting the fixed number of edge pixels. The slope was estimated by the least square method to reduce the detection error. Once a matching point was determined by comparing the feature information of the object and the pattern, the parameters for translation, scaling and rotation were obtained by selecting the longer line of the two which passed through the matching point from left and right sides. Finally, modified Hausdorff Distance has been used to identify the similarity between the object and the given pattern. The multi-label method was developed for recognizing the patterns with more than one label, which performs the modified Hausdorff Distance twice. Experiments have been performed to verify the performance of the proposed algorithm and method for simple target image, complex target image, simple pattern, and complex pattern as well as the partially hidden object. It was proved via experiments that the proposed image matching algorithm for recognizing the object had a good performance of matching.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.1
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• pp.37-45
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• 2002

This paper proposes new features for recognizing telltale bulb in a cluster. A typical feature employed in model-based pattern recognition is polygonal approximation points of object. But recognition using these dominant points has many mismatching counts in small model such as telltale bulb. To reduce mismatching counts, proposed features are the circle distribution of object pixel and the ratio of distance from center to boundary in object. This Paper also proposes new decision function using three features. In simulation result, we make a comparison mismatching counts between recognition using dominant points and the new recognition algorithm using three features.

• Journal of Korea Multimedia Society
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• v.19 no.4
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• pp.681-688
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• 2016

In the intelligent video surveillance, recognizing the moving objects is important issue. However, the conventional moving object recognition methods have some problems, that is, the influence of light, the distinguishing between similar colors, and so on. The recognition methods for the moving objects using depth information have been also studied, but these methods have limit of accuracy because the depth camera cannot measure the depth value accurately. In this paper, we propose a recognition method for the moving objects by using both the depth and the color information. The depth information is used for extracting areas of moving object and then the color information for correcting the extracted areas. Through tests with typical videos including moving objects, we confirmed that the proposed method could extract areas of moving objects more accurately than a method using only one of two information. The proposed method can be not only used in CCTV field, but also used in other fields of recognizing moving objects.

• The KIPS Transactions:PartB
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• v.15B no.2
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• pp.81-86
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• 2008

This paper discusses the problem of partial object recognition in image databases. We propose the method to reconstruct and estimate partially occluded shapes and regions of objects in images from overlapping and cutting. We present the robust method for recognizing partially occluded objects based on symmetry properties, which is based on an ellipse of objects. Our method provides simple techniques to reconstruct occluded regions via a region copy using the symmetry axis within an object. Since our method relies on reconstruction of the object based on the symmetry rather than statistical estimates, it has proven to be remarkably robust in recognizing partially occluded objects in the presence of scale changes, rotation, and viewpoint changes.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.2
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• pp.16-22
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• 2010

This paper proposes the real-time moving object tracking system UAV using color information. Case of object tracking, it have studied to recognizing the moving object or moving multiple objects on the fixed camera. And it has recognized the object in the complex background environment. But, this paper implements the moving object tracking system using the pan/tilt function of the camera after the object's region extraction. To do this tracking system, firstly, it detects the moving object of RGB/HSI color model and obtains the object coordination in acquired image using the compact boundary box. Secondly, the camera origin coordination aligns to object's top&left coordination in compact boundary box. And it tracks the moving object using the pan/tilt function of camera. It is implemented by the Labview 8.6 and NI Vision Builder AI of National Instrument co. It shows the good performance of camera trace in laboratory environment.