• International Journal of Contents
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• v.2 no.3
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• pp.22-26
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• 2006

In this paper we introduce a new circle detection algorithm for occluded on/off pupil and iris boundary extraction. The proposed algorithm employs 7-step processing to detect a center and radius of occluded on/off eye images using the property of the chords. The algorithm deals with two types of occluded pupil and iris boundary information; one is composed of circle-shaped, incomplete objects, which is called occluded on iris images and the other type consists of arc objects in which circular information has partially disappeared, called occluded off iris images. This method shows that the center and radius of iris boundary can be detected from as little as one-third of the occluded on/off iris information image. It is also shown that the proposed algorithm computed the center and radius of the incomplete iris boundary information which has partially occluded and disappeared. Experimental results on RGB images and IR images show that the proposed method has encouraging performance of boundary detection for pupil and iris segmentation. The experimental results show satisfactorily the detection of circle from incomplete circle shape information which is occluded as well as the detection of pupil/iris boundary circle of the occluded on/off image.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.5
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• pp.53-59
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• 2012

Each year, the Forest Service performs measurements to gather statistics regarding on the forest resources and forest character. However, this is not easily obtainable information due to the lack of human accessibility to the survey sample. I proposed a new method to gather data which utilizes the technology of digital imaging. This new method allows over 50% of the sample to be viewable.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.175-180
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• 2018

In this paper, a feature extraction and object recognition algorithm using only morphological operations is proposed. The morphological operations used in feature extraction are erosion and dilation, opening and closing combining erosion and dilation, and morphological edge and skeleton detection operation. In the process of recognizing an object based on features, a pooling operation is applied to reduce the dimension. Among various structuring elements, $3{\times}3$ rhombus, $3{\times}3$ square, and $5{\times}5$ circle are arbitrarily selected in morphological operation process. It has confirmed that the proposed algorithm can be applied in object recognition fields through experiments using Internet images.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.1
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• pp.64-75
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• 2010

This study introduces a complete feature map building method of sonar sensors for mobile robots. This method enhances the reality of feature maps by extracting even circle features as well as line and point features from sonar data. Edge features are, moreover, generated by combining line features close to circle features extracted around comer sites. The uncertainties of the specular reflection phenomenon and wide beam width of sonar data can be, therefore, reduced through this map building method. The experimental results demonstrate a practical validity of the proposed method in those environments.

• Spatial Information Research
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• v.18 no.4
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• pp.13-22
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• 2010

For implementing TMDL(Total Maximum Daily Loading) to adopt more effective management of water pollution, water quality modeling is pre-requisite and such modeling requires the extraction of stream centerline. The institutes responsible for the water quality modeling, however, generates the stream centerline with their own criteria and this lead to low accuracy of the extracted centerline as well as different modeling results for the same watershed. Therefore, this study mainly focused on the development of extraction method of the stream centerline. For that, an automated method has been developed through the integration of the centerline extraction method using a maximum inscribed circle with GIS. The result has shown that the newly developed method could enable to represent more details of the stream topography along with enhanced accuracy compared with conventional extraction method. Furthermore, the new method can afford centerline extraction for the island areas which has been the limitation of the conventional method thereby supporting water quality modeling in a detailed level.

• Journal of IKEEE
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• v.26 no.1
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• pp.104-110
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• 2022

In this paper, we propose a new dataset for AI diagnosis and BLDC motor diagnosis in UAV. In the diagnosis of BLDC motor, PVA(Park's Vector Approach) is difficult to apply due to many ripples of frequency components. However, since the components of ripples are the third harmonics, we propose a method to utilize PVA as circle fitting by applying Savitzky-Golay filter which is excellent for the third harmonics. On the other hand, PVA, a technique to convert from three-phase to two-phase, is always based on the origin during the transformation process. This study demonstrates that the error of the origin and the measured center can be detected and diagnosed in the application process of Circle fitting, and that it can be used as a new data set of AI technology.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.547-550
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• 2009

The object recognition mechanism of human being is not well understood yet. On research of animal experiment using an ape, however, neurons that respond to simple shape (e.g. circle, triangle, square and so on) were found. And Hypothesis has been set up as human being may recognize object as combination of such simple shapes. That mechanism is called Figure Alphabet Hypothesis, and those simple shapes are called Figure Alphabet. As one way to research object recognition algorithm, we focused attention to this Figure Alphabet Hypothesis. Getting idea from it, we proposed the feature extraction algorithm for object recognition. In this paper, we described recognition of binarized images of multifont alphabet characters by the recognition model which combined three-layered neural network in the feature extraction algorithm. First of all, we calculated the difference between the learning image data set and the template by the feature extraction algorithm. The computed finite difference is a feature quantity of the feature extraction algorithm. We had it input the feature quantity to the neural network model and learn by backpropagation (BP method). We had the recognition model recognize the unknown image data set and found the correct answer rate. To estimate the performance of the contriving recognition model, we had the unknown image data set recognized by a conventional neural network. As a result, the contriving recognition model showed a higher correct answer rate than a conventional neural network model. Therefore the validity of the contriving recognition model could be proved. We'll plan the research a recognition of natural image by the contriving recognition model in the future.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1100-1103
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• 1987

In this paper, we report a method for the primitive segments extraction from printed Korean characters without thinning as a preliminary stage to design an efficient recognition system. The primitive segments are defined by fundamental subpatterns which are vertical(I), right sloping(/), left. sloping(\). horizontal(-), and circular segment(o). The circular segment among the five kinds of segment is different from the others in geometrical properties. Therefore, at first, the circular segment is extracted by using the closed circle of the inner boundary and the geometrical characteristics of its outer. Next, linear segments are separated from the character pattern by means of a directional coding method. Finally, primitive segments are extracted from each set of linear segments by using a projection profile which involves the fact whether the segment has branches or not. The experimental results show that this method reduces computation time and storage space in comparision with the existing methods.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.2
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• pp.35-42
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• 2008

This study introduces a robust feature detector for sonar data from a general fixed-type of sonar ring. The detector is composed of a data association filter and a feature extractor. The data association filter removes false returns provided frequently from sonar sensors, and classifies set of data from various objects and robot positions into a group in which all the data are from the same object. The feature extractor calculates the geometries of the feature for the group. We show the possibility of extracting circle feature as well as a line and a point features. The proposed method was applied to a real home environment with a real robot.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.5 no.1
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• pp.87-93
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• 2011

This paper proposes a method for extraction of the gaze point on display using EOG(Electrooculography) signal. Based on the linear property of EOG signal, the proposed method corrects scaling difference, rotation difference and origin difference between coordinate of using EOG signal and coordinate on display, without adjustment using the head movement. The performance of the proposed method was evaluated by measuring the difference between extracted gaze point and displayed circle point on the monitor with 1680*1050 resolution. Experimental results show that the average distance errors at the gaze points are 3%(56pixel) on x-axis, 4%(47pixel) on y-axis, respectively. This method can be used to human computer interface of pointing device for general paralysis patients or HCI for VR game application.