Thumwarin, Pitak

Preferred name

Thumwarin, Pitak

Alternative Name

Thumwarin, P.

Main Affiliation

Music Science and Engineering

pitak.th@kmitl.ac.th

Now showing 1 - 7 of 7

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Iris recognition based on dynamic radius matching of iris image
(2012-10-02)
Thumwarin, P.
;
Chitanont, N.
;
Matsuura, T.
This paper presents iris recognition method based on dynamic radius matching of iris image. First, the iris images are segmented to remove the eyelashes and eyelids. Then the individual feature of the iris image can be extracted by expanding their polar images into Fourier series. The obtained Fourier coefficient is used as the individual features for iris recognition. Moreover, in order to reduce the fluctuation caused by size of pupil and iris, the dynamic radius matching is introduced to calculate the similarity between the iris images. Experimental results were performed on CASIA V1.0 [6] public iris database having 756 iris images from 108 persons. The obtained accuracy rate was 94.8%. © 2012 IEEE.
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On-line writer recognition for Thai numeral
(2002-01-01)
Thumwarin, P.
;
Tangtisanon, P.
;
Murata, S.
;
Matsuura, T.
This paper discusses an on-line writer recognition for Thai numerals. First, a center point of a Thai numeral is determined after normalization. Then the center point is shifted to an origin. Secondly, the distance from the origin to the pen-point position in the handwriting process is measured and the area of a triangle determined from the origin and the two adjacent points of the pen-point position is calculated. Thirdly, the features of pen-point movement in the process are extracted by expanding the time sequence of the above distance and area into Fourier series. Then the features of pen-point movement are represented in terms of Fourier coefficients. Fourthly, in order to describe the handwriting process features, the FIR system with the above coefficients as input and output of the system is introduced. Then the impulse response of the FIR system is used as the feature of handwriting process. Furthermore in order to recognize the writer, K-L expansion (J.T. Tou and R.C. Gonzalez "Pattern Recognition Principles", Addison-Wesley, pp. 269, 1974) of the obtained impulse response is used. In the experiments, the average rates of type I (false rejection) and type II (false acceptance) error were 17.14% and 9.26%, respectively.
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FIR firearm identification system
(2009-01-01)
Thumwarin, P.
;
Prasit, C.
;
Suwanvesh, T.
;
Matsuura, T.
We propose a FIR(Finite impulse response) firearm identification system. The firearm can be identified by using the impulse response of the FIR system characterizing the rotation invariant feature of the cartridge case image. In this case, the rotation invariant feature can be extracted by the magnitude of Fourier coefficients of polar image of the cartridge. Then the obtained Fourier coefficients are used as the input and the output of the FIR system. The impulse response of the FIR system is used as the unique feature for firearm identification. Finally, the firearm can be identified by the Fisher's linear discriminant function. The experimental results are taken to show the effectiveness of the proposed method.
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Firearm identification based on FIR system characterizing rotation invariant feature of cartridge case image
(2008-12-01)
Thumwarin, P.
;
Prasit, C.
;
Boonbumroong, P.
;
Matsuura, T.
We propose firearm identification method based on FIR system characterizing rotation invariant feature of cartridge case image. The rotation invariant feature is represented by the absolute value of Fourier coefficients of polar image on circles with different radii of the cartridge case's primer. Then the FIR(Finite impulse response) system characterizing the rotation invariant feature of cartridge case's primer image is introduced. The absolute value of Fourier coefficients obtained from the polar image on the circles with different radii are used as the input and output of the FIR system, respectively. The obtained impulse response of the FIR system is considered as the unique feature of the individual gun. Finally, a firearm can be identified by using the Fisher's linear discriminant function of the obtained impulse response of the FIR system. The firearm identification experiments are conducted to show the effectiveness of the proposed method. © 2008 IEEE.
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Firearm identification system with rotation invariance
(2010-01-01)
Thumwarin, P.
;
Prasit, C.
;
Yakoompai, K.
;
Matsuura, T.
This paper presents a firearm identification method with rotation invariance. The rotation invariant feature can be extracted by the magnitude of Fourier coefficients of polar image of the cartridge on circles with different radii. Then the fluctuation of the obtained magnitude of Fourier coefficients can be reduced by the FIR(Finite impulse response) Wiener filter. And they are used as the input and the output of the FIR system characterizing the rotation invariant feature of cartridge image. The impulse response of the FIR system is used as the unique feature for firearm identification. Finally, the firearm can be identified by the Fisher's linear discriminant function. The experimental results are given to show the effectiveness of the proposed method. ©ICROS.
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Firearm identification based on rotation invariant feature of cartridge case
(2008-12-01)
Thumwarin, P.
;
Prasit, C.
;
Matsuura, T.
This paper, proposes firearm identification method based on rotation invariant feature of cartridge case image. The rotation invariance feature is represented by the absolute value of Fourier coefficients of polar image of cartridge case on circles with different radii. The absolute value of Fourier coefficients is considered as the individual feature of the particular gun. Finally, the firearm can be identified by the distance between the absolute value of Fourier coefficients obtained from the reference cartridge case and the cartridge case to be identified. The firearm identification experiments are given to show the effectiveness of the proposed method. © 2008 SICE.
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Gait identification based on FIR system characterizing motion of leg
(2013-12-01)
Thumwarin, P.
;
Srisuk, K.
;
Matsuura, T.
This paper presents gait identification method based on Finite Impulse Response (FIR) system characterizing motion of leg. First, the four gait features, area of footstep, angle of footstep, height and width of the human silhouette image, are calculated from the human silhouette image. Then they are expanded into Fourier series to reduce the fluctuation of human body motion. The motion of leg can be characterized by two FIR gait identification systems. For the first FIR system, the Fourier coefficients of the width of human silhouette image and the area of footstep are used as input and output of the system, respectively. For the second FIR system, the Fourier coefficients of the height of the human silhouette image and the angle of footstep are used as input and output of the system, respectively. The obtained impulse responses of the two FIR systems are used as the individual feature for gait identification. The gait identification experiments were performed on CASIA GAIT Dataset B [6], which contains 8,184 gait data for 11 view angles from 124 persons. The average of error rates obtained from 90° view angle was 3.48%. © 2013 IEEE.

Thumwarin, Pitak

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