• Smart Media Journal
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• v.5 no.1
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• pp.24-29
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• 2016

To satisfy the needs of high-level intelligent surveillance system, it shall be able to extract objects and classify to identify precise information on the object. The representative method to identify one's identity is face recognition that is caused a change in the recognition rate according to environmental factors such as illumination, background and angle of camera. In this paper, we analyze the robust face recognition of face image by changing the distance through a variety of experiments. The experiment was conducted by real face images of 1m to 5m. The method of face recognition based on Linear Discriminant Analysis show the best performance in average 75.4% when a large number of face images per one person is used for training. However, face recognition based on Convolution Neural Network show the best performance in average 69.8% when the number of face images per one person is less than five. In addition, rate of low resolution face recognition decrease rapidly when the size of the face image is smaller than $15{\times}15$.

• The Korean Journal of Physiology and Pharmacology
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• v.9 no.1
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• pp.17-22
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• 2005

We examined whether the abnormal EEG state by NMDA receptor blocker MK-801 can be reversed by typical and atypical antipsychotics differentially by comparing their spectral profiles after drug treatment in rats. The spectral profiles produced by typical antipsychotics chlorpromazine (5 mg/kg, i.p.) and haloperidol (0.5 mg/kg, i.p.) were differ from that by atypical antipsychotic clozapine (5 mg/kg, i.p.) in the rats treated with or without MK-801 treatment (0.2 mg/kg, i.p.) which produce behavioral abnormalities like hyperlocomotion and stereotypy. The dissimilarity between the states produced by antipsychotics and the control state was examined with the distance of the location of the canonical variables calculated by stepwise discriminant analysis with the relative band powers as input variables. Although clozapine produced more different state from normal state than typical antipsychotics, clozapine could reverse the abnormal schizophrenic state induced by MK-801 to the state closer to the normal state than the typical antipsychotics. The results suggest that atypical anesthetic can reverse the abnormal schizophrenic state with negative symptom to the normal state better than typical antipsychotic. The results indicate that the multivariate discriminant analysis using the spectral parameters can help differentiate the antipsychotics with different actions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2991-3007
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• 2022

Two dimensional locality preserving projections (2D-LPP) is an improved algorithm of 2D image to solve the small sample size (SSS) problems which locality preserving projections (LPP) meets. It's able to find the low dimension manifold mapping that not only preserves local information but also detects manifold embedded in original data spaces. However, 2D-LPP is simple and elegant. So, inspired by the comparison experiments between two dimensional linear discriminant analysis (2D-LDA) and linear discriminant analysis (LDA) which indicated that matrix based methods don't always perform better even when training samples are limited, we surmise 2D-LPP may meet the same limitation as 2D-LDA and propose a novel matrix exponential method to enhance the performance of 2D-LPP. 2D-MELPP is equivalent to employing distance diffusion mapping to transform original images into a new space, and margins between labels are broadened, which is beneficial for solving classification problems. Nonetheless, the computational time complexity of 2D-MELPP is extremely high. In this paper, we replace some of matrix multiplications with multiple multiplications to save the memory cost and provide an efficient way for solving 2D-MELPP. We test it on public databases: random 3D data set, ORL, AR face database and Polyu Palmprint database and compare it with other 2D methods like 2D-LDA, 2D-LPP and 1D methods like LPP and exponential locality preserving projections (ELPP), finding it outperforms than others in recognition accuracy. We also compare different dimensions of projection vector and record the cost time on the ORL, AR face database and Polyu Palmprint database. The experiment results above proves that our advanced algorithm has a better performance on 3 independent public databases.

• Journal of Dental Rehabilitation and Applied Science
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• v.22 no.4
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• pp.271-281
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• 2006

Long term prediction of surgical result of skeletal class III has not been evaluated adequately because the stability of orthognathic surgery would be affected by not only set back amount of mandible but also many other factors like skeletal pattern, hyoid position, and airway size. The aimof this study is to discriminate the factors which affect the stability of post-treatment result of surgical outcome of sagittal split ramus osteotomy. We have collected 37 patients (male: 17, female: 20) from patients who have been treated at Orthodontic Department in Dankook University. The patients underwent 3 times Cephalometric X-ray taking at pre-, post-orthognathic surgery and after 12 months retention. The subjects were divided into 2 groups (Stable group: 21, Relapse group: 16) according to their relapse amount. We have taken following results from Students t-test and discriminant analysis. The discriminant factors which discern relapse and stable groupe among treatment change variables were BX and Ba-HY. Hyoid bone moved to posterior and inferior position due to surgery and repositioned superiorly and posteriorly during retention period. Skeletal patterns of the relapse group are smaller mandibular plane angle, anterior mandibular position, and greater distance from hyoid bone to cervical bone and mandible respectively.

• Korean journal of applied entomology
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• v.35 no.2
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• pp.104-113
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• 1996

In order to clarify the interspecific variation of Astiphrom jezoense, a morphometric analysis was performed for seven populations using PCA (principle component analysis) and discriminant analysis. As a result of PCA, 25 quantitative characters are grouped into four factors. The characteristics on legs are especially important components both in male and in female. Morphometric analysis indicate that considerable morphological gap is correlated with geographical habitat. Important discriminant characters are MOD (maximum ocellar distance), Fn (first tergite length) in female and MSL (malar space length) in male.

• Animal Systematics, Evolution and Diversity
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• no.nspc2
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• pp.243-250
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• 1988

The wing morphometric characters of P.elaeagni complex feeding on the genus Elaeagnus plants was analysed by the multivariate methods using clustering of generalized distance and discriminant analysis. On the clustering of the species, the effect of sexual differences, seasonal variation and geographic population sensitively appeared . However, four species of this group was precicely divided by the discriminant analysis.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.77-84
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• 2012

Face classification has wide applications in intelligent video surveillance, content retrieval, robot vision, and human-machine interface. Pose and expression changes, and arbitrary illumination are typical problems for face recognition. When the face is captured at a distance, the image quality is often degraded by blurring and noise corruption. This paper investigates the efficacy of multi-classifier decision level fusion for face classification based on the photon-counting linear discriminant analysis with two different cost functions: Euclidean distance and negative normalized correlation. Decision level fusion comprises three stages: cost normalization, cost validation, and fusion rules. First, the costs are normalized into the uniform range and then, candidate costs are selected during validation. Three fusion rules are employed: minimum, average, and majority-voting rules. In the experiments, unfocusing and motion blurs are rendered to simulate the effects of the long distance environments. It will be shown that the decision-level fusion scheme provides better results than the single classifier.

• Journal of Korean Society of Forest Science
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• v.96 no.4
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• pp.387-392
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• 2007

Characteristics of needle morphology and anatomy were examined in 14 populations of Abies nephrolepis (Trautv.) Maxim. and A. koreana Wilson. Additionally we studied the classification index to distinguish between the species by the method of discriminant analysis. Characteristics of needle for A. nephrolepis could be distinguished from those for A. koreana by flatten arrangement, thin and long length for needle form, many stomata row, and marginal position of resin duct Nested ANOVA showed that there were statistically significant differences among populations as well as among individuals within populations in all 9 needle traits. For the needle indices such as needle thickness, number of stomata row, and the distance between resin duct and vascular for both species, variance components among populations were larger than those among individuals within populations. The characteristics that contributed most to the separation of A. nephrolepis and A. koreana according to the discriminant analysis using stepdisc procedures were needle index and thickness of needle, needle arrangement index, distance between resin duct and vascular, and number of stomata row.

• Animal Systematics, Evolution and Diversity
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• v.11 no.4
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• pp.417-434
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• 1995

Three species (0. kinbergi, 0. sarsi and 0 . sarsi vadicola) of the genus Ophiura (Echinodermacta: Ophiuroidea) were sampled from the various localities of Korean waters (Kyonggi Bay in March and September, 1989 and February, 1994; Yellow Sea in September and October, 1992; Southern Sea and Korean Strait in May, 1992; and eastern coasts adjacent to Kangnung in April, July, October, 1993 and January, 1994). Results of the examination of 250 Operational Taxonomical Units (OTUs) are presented based on the 20 morphometric variables to evaluate their taxonomic characters and positions. In cluster analysis, 250 OTUs were divided into 3 phenons (0. kinbergi, 0 . sarsi and 0 . sarsi vadicola) at the Euclidean distance levels of 6.84 and 2 phenons (a phenon composed of 0 . sarsi and 0 . sarsi vadicola and the other of 0. kinbergi) at 7.50. Stepwise discriminant analysis was used in order to produce a good discrimination model and 13 morphological characters (the total number of comb papillae, the number of primary comb papillae and shape of comb papillae (2). etc.) were extracted. The results of canonical discriminant analysis illustrated clear distinction among 3 phenons by the distance of 8.26 between 0 . sarsi and 0. sarsi vadicola, 24.24 between 0 . kinbergi and 0. sarsi vadicola and 21.63 between 0 . kinbergi and 0 . sarsi.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.402-410
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• 2017

For many years, researchers in face description area have been representing and recognizing faces based on different methods that include subspace discriminant analysis, statistical learning and non-statistics based approach etc. But still automatic face recognition remains an interesting but challenging problem. This paper presents a novel and efficient face image representation method based on Optimized Local Ternary Pattern (OLTP) texture features. The face image is divided into several regions from which the OLTP texture feature distributions are extracted and concatenated into a feature vector that can act as face descriptor. The recognition is performed using nearest neighbor classification method with Chi-square distance as a similarity measure. Extensive experimental results on Yale B, ORL and AR face databases show that OLTP consistently performs much better than other well recognized texture models for face recognition.