Browsing by Author "Chen, LF"

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A new LDA-based face recognition system which can solve the small sample size problem
(2000-10-01)
Chen, LF
;
Liao, HYM
;
Ko, MT
;
Lin, JC
;
Yu, GJ
A new LDA-based face recognition system is presented in this papal. Linear discriminant analysis (LDA) is one of the most popular linear projection techniques for feature extraction. The major drawback of applying LDA is that it may encounter the small sample size problem. In this paper, we propose a new LDA-based technique which can solve the small sample size problem. We also prove that the most expressive vectors derived ill the null space of the within-class scatter matrix using principal component analysis (PCA) are equal to the optimal discriminant vectors derived in the: original space using LDA. The experimental results show that the new LDA process improves the performance of a face recognition system significantly. (C) 2000 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
Grain-boundary surface states of (Ba, Pb)TiO3 positive temperature coefficient ceramics doped with different additives and its influence on electrical properties
(1996-09-01)
Chen, LF
;
Tseng, TY
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
The electrical properties of positive temperature coefficient of resistance (PTCR) ceramics of composition (Ba, Pb, La)TiO3 prepared from commercial BaTiO3 powders doped with different additives were studied. It was proposed here that different additives might have generated the corresponding number of possible surface states, such as, the segregation behavior of Mn ions (3d transition metal ions), oxygen adsorption reaction resulting from BN addition, the action of Ca replacing the Ti sites (Ca''(Ti)), and the natural intrinsic defects (V''(Ba), V''(Pb)). In general, some experimental derivations were also offered that majority of the surface states, which possessed their individual surface energy level, possibly coexisted onto the grain surface. Utilizing the concept of the coexistence of different types of surface states in the energy band, a satisfactory point-to-point agreement was obtained between the measured result and calculated values for the resistivity curve. Our experimental results were analyzed based on the terms of the Heywang-Jonker model and have shown that the assumption of a Hewang barrier was a reasonable approach for our set of samples; however, the distribution and types of grain-boundary acceptor states classification were required.
Grain-boundary surface states of (Ba, Pb)TiO3 positive temperature coefficient ceramics doped with different additives and its influence on electrical properties
(1996-09-01)
Chen, LF
;
Tseng, TY
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
The electrical properties of positive temperature coefficient of resistance (PTCR) ceramics of composition (Ba, Pb, La)TiO3 prepared from commercial BaTiO3 powders doped with different additives were studied. It was proposed here that different additives might have generated the corresponding number of possible surface states, such as, the segregation behavior of Mn ions (3d transition metal ions), oxygen adsorption reaction resulting from BN addition, the action of Ca replacing the Ti sites (Ca''(Ti)), and the natural intrinsic defects (V''(Ba), V''(Pb)). In general, some experimental derivations were also offered that majority of the surface states, which possessed their individual surface energy level, possibly coexisted onto the grain surface. Utilizing the concept of the coexistence of different types of surface states in the energy band, a satisfactory point-to-point agreement was obtained between the measured result and calculated values for the resistivity curve. Our experimental results were analyzed based on the terms of the Heywang-Jonker model and have shown that the assumption of a Hewang barrier was a reasonable approach for our set of samples; however, the distribution and types of grain-boundary acceptor states classification were required.
ICA-based spatiotemporal approach for single-trial analysis of postmovement MEG beta synchronization
(2003-12-01)
Lee, PL
;
Wu, YT
;
Chen, LF
;
Chen, YS
;
Cheng, CM
The extraction of event-related oscillatory neuromagnetic activities from single-trial measurement is challenging due to the non-phase-locked nature and variability from trial to trial. The present study presents a method based on independent component analysis (ICA) and the use of a template-based correlation approach to extract Rolandic beta rhythm from magnetoencephalographic (MEG) measurements of right finger lifting. A single trial recording was decomposed into a set of coupled temporal independent components and corresponding spatial maps using ICA and the reactive beta frequency band for each trial identified using a two-spectrum comparison between the postmovement interval and a reference period. Task-related components survived dual criteria of high correlation with both the temporal and the spatial templates with an acceptance rate of about 80%. Phase and amplitude information for noise-free MEG beta activities were preserved not only for optimal calculation of beta rebound (event-related synchronization) but also for profound penetration into subtle dynamics across trials. Given the high signal-to-noise ratio (SNR) of this method, various methods of source estimation were used on reconstructed single-trial data and the source loci coherently anchored in the vicinity of the primary motor area. This method promises the possibility of a window into the intricate brain dynamics of motor control mechanisms and the cortical pathophysiology of movement disorder on a trial-by-trial basis. (C) 2003 Elsevier Inc. All rights reserved.
Wavelet-based optical flow estimation
(2000)
Chen, LF
;
Lin, JC
;
Liao, HYM
;
資訊工程學系
;
Department of Computer Science
In this paper, a new algorithm for accurate optical flow estimation using discrete wavelet approximation is proposed. In traditional gradient-based approaches, the computation of optical flow depends on minimizing the image and smoothness constraints. The proposed method takes advantages of the nature of wavelet theory, which can efficiently and accurately represent "things," to model optical flow vectors and image related functions. Each flow vector and image function will be represented by linear combinations of wavelet basis functions. From such wavelet-based approximation, the leading coefficients of these basis functions carry the global information of the approximated "things." The proposed method cab successfully convert the problem of minimizing a constraint function into that of solving a linear system of a quadratic and convex function of wavelet coefficients. Once all the corresponding coefficients are decided, the flow vectors can be determined accordingly. Experiments have been conducted on both synthetic and real image sequences and the results have reflected that our approach outperformed the existing methods in terms of accuracy.
Wavelet-based optical flow estimation
(2002-01-01)
Chen, LF
;
Liao, HYM
;
Lin, JC
;
資訊工程學系
;
Department of Computer Science
In this paper, a new algorithm for accurate optical flow (OF) estimation using discrete wavelet approximation is proposed. The computation of OF depends on minimizing the image and smoothness constraints. The proposed method takes advantages of the nature of wavelet theory, which can efficiently and accurately approximate any function. OF vectors and image functions are represented by means of linear combinations of scaling basis functions. Based on such wavelet-based approximation, the leading coefficients of these basis functions carry global information about the approximated functions. The proposed method can successfully convert the problem of minimizing a constraint function into that of solving a linear system of a quadratic and convex function of scaling coefficients. Once all the corresponding coefficients are determined, the flow vectors can be obtained accordingly. Experiments have been conducted on both synthetic and real image sequences. In terms of accuracy, the results show that our approach outperforms the existing methods which adopted the same objective function as ours.
Why recognition in a statistics-based face recognition system should be based on the pure face portion: a probabilistic decision-based proof
(2001-07-01)
Chen, LF
;
Liao, HYM
;
Lin, JC
;
Han, CC
;
資訊工程學系
It is evident that the process of face recognition, by definition, should be based on the content of a face. The problem is: what is a "face"? Recently, a state-of-the-art statistics-based face recognition system, the PCA plus LDA approach, has been proposed (Swets and Weng, IEEE Trans. pattern. Anal. Mach. Intell. 18 (8) (1996) 831-836). However, thr authors used "face" images that included hail, shoulders, face and background. Our intuition tells us that only a recognition process based on a "pure" Face portion can be called face recognition. The mixture of irrelevant data may result in an incorrect set of decision boundaries. In this paper, we propose a statistics-based technique to quantitatively prove our assertion. For the purpose of evaluating how the different portions of a Face image will influence the recognition results, a hypothesis testing model is proposed. We then implement the above mentioned face recognition system and use the proposed hypothesis testing model to evaluate the system. Experimental results show that the influence of the "real"-face portion is much less than that of the nonface portion. This outcome confirms quantitatively that recognition in a statistics-based face recognition system should be based solely on the "pure" face portion. (C) 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.