• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.4
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• pp.1-11
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• 2008

In this paper, we propose the new eye detection method by using adaboost (adaptive boosting) method. Also, to reduce the false alarm rate which identifies the non-eye region as genuine eye that is the Problems of previous method using conventional adaboost, we proposed the post processing methods which used the cornea specular reflection and determined the optimized ratio of eye detecting box. Based on detected eye region by using adaboost, we performed the double circular edge detector for localizing a pupil and an iris region at the same time. Experimental results showed that the accuracy of eye detection was about 98% and the processing time was less than 1 second in mobile device.

• International journal of thyroidology
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• v.11 no.2
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• pp.92-98
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• 2018

Intraoperative identification and localization of parathyroid glands are crucial step in preventing postoperative hypocalcemia during thyroid and parathyroid surgery. If there is a method to predict the parathyroid's location rather than detecting and verifying with naked eye, it would make the operator easier to find and identify the parathyroid. Recently, near-infrared light imaging technologies have been introduced in the fields of thyroid and parathyroid surgery to predict the localization of the parathyroid. These are being conducted in two ways: autofluorescence imaging with a unique intrinsic fluorophore in the parathyroid tissues and fluorescence imaging with external fluorescence materials specially absorbed into parathyroid tissues. We are suggest that parathyroid glands can be detected by surgeon with NIR autofluorescence imaging even if they are covered by fibrofatty tissues before they are detected by surgeon's naked eye. These novel techniques are very useful to identify and preserve parathyroid glands during thyroidectomy. In this article, we reviewed the latest papers that describe autofluorescence imaging and exogenous ICG fluorescence imaging of parathyroid glands during thyroid and parathyroid surgery.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.478-484
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• 2009

Automatic speech recognition(ASR) is attractive technique in trend these day that seek convenient life. Although many approaches have been proposed for ASR but the performance is still not good in noisy environment. Now-a-days in the state of art in speech recognition, ASR uses not only the audio information but also the visual information. In this paper, We present a novel lip detection method for visual speech recognition in mobile environment. In order to apply visual information to speech recognition, we need to extract exact lip regions. Because eye-detection is more easy than lip-detection, we firstly detect positions of left and right eyes, then locate lip region roughly. After that we apply K-means clustering technique to devide that region into groups, than two lip corners and lip center are detected by choosing biggest one among clustered groups. Finally, we have shown the effectiveness of the proposed method through the experiments based on samsung AVSR database.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.178-186
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• 2003

Recently, many researchers have been interested in biometric systems such as fingerprint, handwriting, key-stroke patterns and human iris. From the viewpoint of reliability and robustness, iris recognition is the most attractive biometric system. Moreover, the iris recognition system is a comfortable biometric system, since the video image of an eye can be taken at a distance. In this paper, we discuss human iris recognition, which is based on accurate iris localization, robust feature extraction, and Neural Network classification. The iris region is accurately localized in the eye image using a multiresolution active snake model. For the feature representation, the localized iris image is decomposed using wavelet transform based on dyadic Haar wavelet. Experimental results show the usefulness of wavelet transform in comparison to conventional Gabor transform. In addition, we present a new method for setting initial weight vectors in competitive learning. The proposed initialization method yields better accuracy than the conventional method.

• Korean Journal of Psychosomatic Medicine
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• v.15 no.2
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• pp.73-80
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• 2007

Anumber of prior studies have reported eye movement dysfunction in patients with dementia. The eye movement test which is non-invasive can evaluate the local brain function quantitatively. Therefore, it can be a useful method for characterizing regional brain abnormalities of patients with dementia. The aim of this paper is to review the literatures on eye movement abnormalities in dementia patients. Saccade system dysfunctions in Alzheimer disease include increased latency, reduced accuracy, and increased antisaccade error rates. Patients with frontotemporal dementia showed impaired reflexive saccade inhibition and increased latency and errors of antisaccade task. And delayed initiation of voluntary saccades, slow saccades, and increased errors and latency on antisaccade task were found in Huntington's disease. Patients with Parkinson’s disease dementia and dementia with Lewy bodies have characteristics of impaired in both reflexive saccade execution and complex saccade performance. However, there were few reports of abnormal eye movements in Creutzfeldt-Jakob disease; they could be found at the later stages after symptoms of dementia came to be evident, and secondary to cerebellar and vestibular involvement. Slowing of saccades and hypometric saccades might precede the supranuclear limitation of vertical gaze in PSP. Dysfunction of voluntary eyelid movements was a characteristic finding of PSP as well. In conclusion, patients with dementia can show various abnormal eye movements and they are related with cortial and subcortical brain dysfunctions. The research on localization of brain relevant to each symptom can promise more clinical implications of eye movement of dementia.

• Journal of the Optical Society of Korea
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• v.13 no.1
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• pp.116-122
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• 2009

In this paper, a robust method is developed to locate the irises of both eyes. The method doesn't put any restrictions on the background. The method is based on the AdaBoost algorithm for face and eye candidate points detection. Candidate points are tuned such that two candidate points are exactly in the centers of the irises. Mean crossing function and convolution template are proposed to filter out candidate points and select the iris pair. The advantage of using this kind of hybrid method is that AdaBoost is robust to different illumination conditions and backgrounds. The tuning step improves the precision of iris localization while the convolution filter and mean crossing function reliably filter out candidate points and select the iris pair. The proposed structure is evaluated on three public databases, Bern, Yale and BioID. Extensive experimental results verified the robustness and accuracy of the proposed method. Using the Bern database, the performance of the proposed algorithm is also compared with some of the existing methods.

• International Journal of Automotive Technology
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• v.7 no.3
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• pp.361-367
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• 2006

This paper describes a novel stereo vision based localization of free parking site, which recognizes the target position of automatic parking system. Pixel structure classification and feature based stereo matching extract the 3D information of parking site in real time. The pixel structure represents intensity configuration around a pixel and the feature based stereo matching uses step-by-step investigation strategy to reduce computational load. This paper considers only parking site divided by marking, which is generally drawn according to relevant standards. Parking site marking is separated by plane surface constraint and is transformed into bird's eye view, on which template matching is performed to determine the location of parking site. Obstacle depth map, which is generated from the disparity of adjacent vehicles, can be used as the guideline of template matching by limiting search range and orientation. Proposed method using both the obstacle depth map and the bird's eye view of parking site marking increases operation speed and robustness to visual noise by effectively limiting search range.

• Journal of Veterinary Clinics
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• v.40 no.5
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• pp.360-364
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• 2023

A 7-year-old castrated male Yorkshire Terrier presented for a palpable mass of the right neck with ophthalmic signs of conjunctival hyperemia and anisocoria with fixed mydriatic pupil of the right eye. Clinical examination findings included the absence of direct and consensual pupillary light reflexes, external and internal ophthalmoplegia, and corneal hypoesthesia with incomplete blinking of the right eye. Magnetic resonance imaging and computed tomography revealed a mass extending from the right cavernous sinus to the orbital fissure with neighboring bone lysis. Cytological examination of fine-needle aspiration samples of the mass revealed a neuroendocrine tumor. The owner declined further diagnosis and did not wish to care for the dog receiving chemotherapy. This study describes the importance of investigating neuro-ophthalmic findings, which might provide clues for the localization of lesions, including tumors, to aid in diagnosis.

• Korean Journal of Radiology
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• v.24 no.3
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• pp.247-258
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• 2023

Objective: To localize the neuroanatomical substrate of rapid eye movement sleep behavior disorder (RBD) and to investigate the neuroanatomical locational relationship between RBD and α-synucleinopathy neurodegenerative diseases. Materials and Methods: Using a systematic PubMed search, we identified 19 patients with lesions in different brain regions that caused RBD. First, lesion network mapping was applied to confirm whether the lesion locations causing RBD corresponded to a common brain network. Second, the literature-based RBD lesion network map was validated using neuroimaging findings and locations of brain pathologies at post-mortem in patients with idiopathic RBD (iRBD) who were identified by independent systematic literature search using PubMed. Finally, we assessed the locational relationship between the sites of pathological alterations at the preclinical stage in α-synucleinopathy neurodegenerative diseases and the brain network for RBD. Results: The lesion network mapping showed lesions causing RBD to be localized to a common brain network defined by connectivity to the pons (including the locus coeruleus, dorsal raphe nucleus, central superior nucleus, and ventrolateral periaqueductal gray), regardless of the lesion location. The positive regions in the pons were replicated by the neuroimaging findings in an independent group of patients with iRBD and it coincided with the reported pathological alterations at post-mortem in patients with iRBD. Furthermore, all brain pathological sites at preclinical stages (Braak stages 1-2) in Parkinson's disease (PD) and at brainstem Lewy body disease in dementia with Lewy bodies (DLB) were involved in the brain network identified for RBD. Conclusion: The brain network defined by connectivity to positive pons regions might be the regulatory network loop inducing RBD in humans. In addition, our results suggested that the underlying cause of high phenoconversion rate from iRBD to neurodegenerative α-synucleinopathy might be pathological changes in the preclinical stage of α-synucleinopathy located at the regulatory network loop of RBD.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05a
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• pp.106-109
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• 2004

Many reported methods assume that the faces in an image or an image sequence have been identified and localization. Face detection from image is a challenging task because of variability in scale, location, orientation and pose. In this paper, we present an efficient linear discriminant for multi-view face detection. Our approaches are based on linear discriminant. We define training data with fisher linear discriminant to efficient learning method. Face detection is considerably difficult because it will be influenced by poses of human face and changes in illumination. This idea can solve the multi-view and scale face detection problem poses. Quickly and efficiently, which fits for detecting face automatically. In this paper, we extract face using fisher linear discriminant that is hierarchical models invariant pose and background. We estimation the pose in detected face and eye detect. The purpose of this paper is to classify face and non-face and efficient fisher linear discriminant..