• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.3
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• pp.575-591
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• 2011

We present a novel active contour-based two-pass approach to extract smooth feature regions from a triangular mesh. In the first pass, an active contour formulated in level-set surfaces is devised to extract feature regions with rough boundaries. In the second pass, the rough boundary curve is smoothed by minimizing internal energy, which is derived from its curvature. The separation of the extraction and smoothing process enables us to extract feature regions with smooth boundaries from a triangular mesh without user's initial model. Furthermore, smooth feature curves can also be obtained by skeletonizing the smooth feature regions. We tested our algorithm on facial models and proved its excellence.

• Journal of the Korean Graphic Arts Communication Society
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• v.8 no.1
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• pp.71-87
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• 1990

This paper presents a simple algorithm to obtain three dimensional information of an object. In the preprocessing of the stereo matching,feature point informations of stero image must be less sensitive to noise and well liked the correspondance problem. This paper described a simple technique of struture feature extraction of 3-D object and used edge-end point expanding method for unconnected line instade of Hough transform. The feature such as corner point and their angles are used for matching problem. The experimental results show that the described algorithm is a useful method for stereo correspondence problem.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.2
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• pp.46-54
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• 2012

We propose a continuously varying contact pressure(CVCP)-adaptive feature extraction algorithm for pulse diagnostic analysis. The CVCP method measures the pulse waveform with continuously increasing contact pressure(CP). This method offer a high resolution signal of the pulse waveform amplitude(PWA) as a function of the contact pressure. Therefore it enables us to overcome the limitation of commercially available pulse-taking devices whose analysis rely on a few number of PWA-CP pairs. We show that an efficient feature extraction algorithm which covers the features of the CVCP-method can be developed by sequentially applying Fast Fourier Transform, peak detection by center-to-edges method, baseline drift removal, detection of the percussion wave upstroke by intersecting tangent method and detection of the analysis region. Finally, by a clinical study with 30 subjects, we show that our CVCP-adaptive feature extraction algorithm detected the upstroke with accuracy of 99.46% and sensitivity of 99.51%, which were about 4.82% and 2.46% increases respectively, compared to a conventional feature extraction method. The proposed CVCP method and the CVCP-adaptive feature extraction algorithm are expected to improve the accuracy in the pulse diagnostic algorithms such as floating/sunken pulse qualities and deficient/excess pulse qualities.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.181-183
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• 2004

In this paper, We proposed an algorithm which extraction iris region from 2D image. Our method is composed of three parts : internal boundary defection and external boundary detection. Since eyelid and eyelash cover part of the boundary and the size of iris changes continuously, it is difficult to extract iris region accurately. For the interior and exterior boundary detection, we used partial differentiation of histogram. Performance of the proposed algorithm is tested and evaluated using 360 iris image samples.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.38-43
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• 2022

In this study, there are many difficulties in defining and judging creative people because there is no systematic analysis method using accurate standards or numerical values. Analyze and judge whether In the previous study, A study on the application of rule success cases through machine learning algorithm extraction, a case study was conducted to help verify or confirm the psychological personality test and aptitude test. We proposed a solution to a research problem in psychology using machine learning algorithms, Data Mining's Cross Industry Standard Process for Data Mining, and CRISP-DM, which were used in previous studies. After that, this study proposes a solution that helps to judge creative people by applying the feature selection algorithm. In this study, the accuracy was found by using seven feature selection algorithms, and by selecting the feature group classified by the feature selection algorithms, and the result of deriving the classification result with the highest feature obtained through the support vector machine algorithm was obtained.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.251-252
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• 2007

The thesis proposed the Text Extraction Algorithm which is a text extraction algorithm which uses the Coiflet Wavelet, YCbCr Color model and the close curve edge feature of adaptive LoG Operator in order to complement the demerit of the existing research which is weak in complexity of background, variety of light and disordered line and similarity of text and background color. This thesis is simulated with natural images which include naturally text area regardless of size, resolution and slant and so on of image. And the proposed algorithm is confirmed to an excellent by compared with an existing extraction algorithm in same image.

• Journal of Computational Design and Engineering
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• v.2 no.2
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• pp.79-87
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• 2015

Surface segmentation and edge feature lines extraction from fractured fragments of relics are essential steps for computer assisted restoration of fragmented relics. As these fragments were heavily eroded, it is a challenging work to segment surface and extract edge feature lines. This paper presents a novel method to segment surface and extract edge feature lines from triangular meshes of irregular fractured fragments. Firstly, a rough surface segmentation is accomplished by using a clustering algorithm based on the vertex normal vector. Secondly, in order to differentiate between original and fracture faces, a novel integral invariant is introduced to compute the surface roughness. Thirdly, an accurate surface segmentation is implemented by merging faces based on face normal vector and roughness. Finally, edge feature lines are extracted based on the surface segmentation. Some experiments are made and analyzed, and the results show that our method can achieve surface segmentation and edge extraction effectively.

• Proceedings of the KSRS Conference
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• v.2
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• pp.643-646
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• 2006

This paper addresses the approach to extract linear features from satellite imagery using an efficient segmentation method. The extraction of linear features from satellite images has been the main concern of many scientists. There is a need to develop a more capable and cost effective method for the Iranian map revision tasks. The conventional approaches for producing, maintaining, and updating GIS map are time consuming and costly process. Hence, this research is intended to investigate how to obtain linear features from SPOT satellite imagery. This was accomplished using a discontinuity-based segmentation technique that encompasses four stages: low level bottom-up, middle level bottom-up, edge thinning and accuracy assessment. The first step is geometric correction and noise removal using suitable operator. The second step includes choosing the appropriate edge detection method, finding its proper threshold and designing the built-up image. The next step is implementing edge thinning method using mathematical morphology technique. Lastly, the geometric accuracy assessment task for feature extraction as well as an assessment for the built-up result has been carried out. Overall, this approach has been applied successfully for linear feature extraction from SPOT image.

• Journal of the Semiconductor & Display Technology
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• v.15 no.2
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• pp.61-65
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• 2016

Facial feature detection is a fundamental function in the field of computer vision such as security, bio-metrics, 3D modeling, and face recognition. There are many algorithms for the function, active shape model is one of the most popular local texture models. This paper addresses issues related to face detection, and implements an efficient extraction algorithm for extracting the facial feature points to use on iOS platform. In this paper, we extend the original ASM algorithm to improve its performance by four modifications. First, to detect a face and to initialize the shape model, we apply a face detection API provided from iOS CoreImage framework. Second, we construct a weighted local structure model for landmarks to utilize the edge points of the face contour. Third, we build a modified model definition and fitting more landmarks than the classical ASM. And last, we extend and build two-dimensional profile model for detecting faces within input images. The proposed algorithm is evaluated on experimental test set containing over 500 face images, and found to successfully extract facial feature points, clearly outperforming the original ASM.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1279-1287
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• 2006

The purpose of this paper is to present a new algorithm for extracting the consensus pattern, or motif from sequence belonging to the same family. Two methods are considered for feature interval partitioning based on equal probability and equal width interval partitioning. C2H2 zinc finger protein and epidermal growth factor protein sequences are used to demonstrate the effectiveness of the proposed algorithm for motif extraction. For two protein families, the equal width interval partitioning method performs better than the equal probability interval partitioning method.