• Journal of Information Processing Systems
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• v.9 no.1
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• pp.173-188
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• 2013

In Facial Expression Recognition Systems (FERS), only particular regions of the face are utilized for discrimination. The areas of the eyes, eyebrows, nose, and mouth are the most important features in any FERS. Applying facial features descriptors such as the local binary pattern (LBP) on such areas results in an effective and efficient FERS. In this paper, we propose an automatic facial expression recognition system. Unlike other systems, it detects and extracts the informative and discriminant regions of the face (i.e., eyes, nose, and mouth areas) using Haar-feature based cascade classifiers and these region-based features are stored into separate image files as a preprocessing step. Then, LBP is applied to these image files for facial texture representation and a feature-vector per subject is obtained by concatenating the resulting LBP histograms of the decomposed region-based features. The one-vs.-rest SVM, which is a popular multi-classification method, is employed with the Radial Basis Function (RBF) for facial expression classification. Experimental results show that this approach yields good performance for both frontal and near-frontal facial images in terms of accuracy and time complexity. Cohn-Kanade and JAFFE, which are benchmark facial expression datasets, are used to evaluate this approach.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.617-624
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• 2004

This paper describes a new facial feature localization method that uses Adjacent Depth Differences(ADD) in 3D facial surface. In general, human recognize the extent of deepness or shallowness of region relatively, in depth, by comparing the neighboring depth information among regions of an object. The larger the depth difference between regions shows, the easier one can recognize each region. Using this principal, facial feature extraction will be easier, more reliable and speedy. 3D range images are used as input images. And ADD are obtained by differencing two range values, which are separated at a distance coordinate, both in horizontal and vertical directions. ADD and input image are analyzed to extract facial features, then localized a nose region, which is the most prominent feature in 3D facial surface, effectively and accurately.

• Journal of the Korean Solar Energy Society
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• v.32 no.5
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• pp.31-40
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• 2012

This paper introduces a methodology for NREL 5MW wind turbine, which is the variable speed and variable pitch(VSVP) control system. This control strategy maximizes the power extraction capability from the wind in the low wind speed region and regulates the wind turbine power as the rated one for the high wind speed region. Also, pitch control efficiency is raised by using pitch scheduling.Torque schedule is made of torque table depending on the rotor speed. Torque control is used for vertical region in a torque-rotor speed chart. In addition to these, mechanical loads reduction using a drive train damper and exclusion zone on a torque schedule is tried. The NREL 5MW wind turbine control strategy is comprised by the generator torque and blade pitch control. Finally, proposed control system is verified through GH Bladed simulation.

• Current Optics and Photonics
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• v.1 no.6
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• pp.587-597
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• 2017

The extraction of the valid measurement region from the interference fringe pattern is a significant step when measuring gear tooth flank form deviation with grazing incidence interferometry, which will affect the measurement accuracy. In order to overcome the drawback of the conventionally used method in which the object image pattern must be captured, an improved segmentation approach is proposed in this paper. The interference fringe patterns feature, which is smoothed by the nonlinear diffusion, would be extracted by the structure tensor first. And then they are incorporated into the vector-valued Chan-Vese model to extract the valid measurement region. This method is verified in a variety of interference fringe patterns, and the segmentation results show its feasibility and accuracy.

• Journal of Information Technology and Architecture
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• v.10 no.1
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• pp.113-122
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• 2013

In this paper, we propose the method that automatically corrects the composition of a picture stylishly as well as reliably by cropping pictures based on the Rule of Thirds. The region of interest (ROI) is extracted from a picture by applying the Saliency Map and the Image Segmentation technology, the composition of the photo is amended based on this area to satisfy the Rule of Thirds. In addition, since the face region of the person is added to ROI by the Face Detection technique and the composition is amended by the various scenario according to ROI, the little more natural picture is acquired. The experimental result shows that the photo of the corrected composition was naturally amended compared with the original photo.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.11
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• pp.2051-2057
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• 2007

In Oriental medicine, the status of a tongue is the important indicator to diagnose one's health like physiological and clinicopathological changes of inner parts of the body. The method of tongue diagnosis is not only convenient but also non-invasive and widely used in Oriental medicine. However, tongue diagnosis is affected by examination circumstances a lot like a light source, patient's posture and doctor's condition. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, segmenting a tongue is inevitable but difficult since the colors of a tongue, lips and skin in a mouth are similar. The proposed method includes preprocessing, graph-based over-segmentation, detecting positions with a local minimum over shading, detecting edge with color difference and estimating edge geometry from the probable structure of a tongue, where preprocessing performs down-sampling to reduce computation time, histogram equalization and edge enhancement. A tongue was segmented from a face image with a tongue from a digital tongue diagnosis system by the proposed method. According to three oriental medical doctors' evaluation, it produced the segmented region to include effective information and exclude a non-tongue region. It can be used to make an objective and standardized diagnosis.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.5
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• pp.519-524
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• 2006

Segmentation for the region of nucleus in the image of uterine cervical cytodiagnosis is known as the most difficult and important part in the automatic cervical cancer recognition system. In this paper, the region of nucleus is extracted from an image of uterine cervical cytodiagnosis using the fuzzy grey morphology operation. The characteristics of the nucleus are extracted from the analysis of morphemetric features, densitometric features, colormetric features, and textural features based on the detected region of nucleus area. The classification criterion of a nucleus is defined according to the standard categories of the Bethesda system. The enhanced fuzzy ART algorithm is used to the extracted nucleus and the results show that the proposed method is efficient in nucleus recognition and uterine cervical Pap-Smears extraction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4005-4025
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• 2019

Copy-move forgery (CMF) in digital images is a detrimental tampering of artefacts that requires precise detection and analysis. CMF is performed by copying and pasting a part of an image into other portions of it. Despite several efforts to detect CMF, accurate identification of noise, blur and rotated region-mediated forged image areas is still difficult. A novel algorithm is developed on the basis of quaternion polar complex exponential transform (QPCET) to detect CMF and is conducted involving a few steps. Firstly, the suspicious image is divided into overlapping blocks. Secondly, invariant features for each block are extracted using QPCET. Thirdly, the duplicated image blocks are determined using k-dimensional tree (kd-tree) block matching. Lastly, a new technique is introduced to reduce the flat region-mediated false matches. Experiments are performed on numerous images selected from the CoMoFoD database. MATLAB 2017b is used to employ the proposed method. Metrics such as correct and false detection ratios are utilised to evaluate the performance of the proposed CMF detection method. Experimental results demonstrate the precise and efficient CMF detection capacity of the proposed approach even under image distortion including rotation, scaling, additive noise, blurring, brightness, colour reduction and JPEG compression. Furthermore, our method can solve the false match problem and outperform existing ones in terms of precision and false positive rate. The proposed approach may serve as a basis for accurate digital image forensic investigations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.815-823
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• 2004

A hue-based attention operator and a combinational integral projection function(CIPF) are proposed to extract the normalized regions of face and facial features robustly against illumination variation. The face candidate regions are efficiently detected by using skin color filter, and the eyes are located accurately nil robustly against illumination variation by applying the proposed hue- and symmetry-based attention operator to the face candidate regions. And the faces are confirmed by verifying the eyes with the color-based eye variance filter. The proposed CIPF, which combines the weighted hue and intensity, is applied to detect the accurate vertical locations of the eyebrows and the mouth under illumination variations and the existence of mustache. The global face and its local feature regions are exactly located and normalized based on these accurate geometrical information. Experimental results on the AR face database［8］ show that the proposed eye detection method yields better detection rate by about 39.3% than the conventional gray GST-based method. As a result, the normalized facial features can be extracted robustly and consistently based on the exact eye location under illumination variations.

• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.87-101
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• 2002

In this paper, we proposes the car plate recognition and describe the parking control system using the proposed car plate recognition algorithm. The car plate recognition system using color information and fuzzy c-means algorithm consists of the extraction part of a car plate from a car image and the recognition part of characters in the extracted car plate. This paper eliminates green noise from car image using the mode smoothing and extract plate region using green and white information of RGB color. The codes of extracted plate region is extracted by histogram based approach method and is recognized by fuzzy c-means algorithm. For experimental, we tested 80 car images. We shows that the proposed extraction method is better than that from the color information of RGB and HSI, respectively. So, we can know that the proposed car plate recognition method using fuzzy c-means algorithm was very efficient. We develop the parking control system using the proposed car plate recognition method, which showed performance improvement by the experimental results.