• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1157-1165
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• 2017

2-D complex Gabor filtering has found numerous applications in the fields of computer vision and image processing. Especially, in some applications, it is often needed to compute 2-D complex Gabor filter bank consisting of the 2-D complex Gabor filtering outputs at multiple orientations and frequencies. Although several approaches for fast 2-D complex Gabor filtering have been proposed, they primarily focus on reducing the runtime of performing the 2-D complex Gabor filtering once at specific orientation and frequency. To obtain the 2-D complex Gabor filter bank output, existing methods are repeatedly applied with respect to multiple orientations and frequencies. In this paper, we propose a novel approach that efficiently computes the 2-D complex Gabor filter bank by reducing the computational redundancy that arises when performing the Gabor filtering at multiple orientations and frequencies. The proposed method first decomposes the Gabor basis kernels to allow a fast convolution with the Gaussian kernel in a separable manner. This enables reducing the runtime of the 2-D complex Gabor filter bank by reusing intermediate results of the 2-D complex Gabor filtering computed at a specific orientation. Experimental results demonstrate that our method runs faster than state-of-the-arts methods for fast 2-D complex Gabor filtering, while maintaining similar filtering quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7C
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• pp.598-603
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• 2010

In this paper, we work for Lipreading using visual information for ship environment. Lipreading is studied for using image information including lips of a speaker at the existing speech recognition system. This technique is a compensation method to increase recognition rate decreasing remarkably in noisy circumstances. Proposed way improved the rate of recognition improving methode of preprocessing using the Gabor Filter for Ship Environment. The experiment were carried out under changing of light with time in the ship environment with lip image. For Comparing with recognition, make a compare with between method of lip region of interest (ROI) before Gabor filtering and after Gabor filtering. In the case of using method of lip ROI before Gabor filtering, the result of the experiments applying to the proposed ways recognition resulting in 44% of recognition.

• Journal of IKEEE
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• v.18 no.2
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• pp.234-239
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• 2014

This paper proposes a new automatic detection method to inspect mura defects on display film surface using morphological image processing and labeling. This automatic detection method for mura defects on display films comprises 3 phases of preprocessing with morphological image processing, Gabor filtering, and labeling. Since distorted results could be obtained with the presence of non-uniform illumination, preprocessing step reduces illumination components using morphological image processing. In Gabor filtering, mura images are created with binary coded mura components using Gabor filters. Subsequently, labeling is a final phase of finding the mura defect area using the difference between large mura defects and values in the periphery. To evaluate the accuracy of the proposed detection method, detection rate was assessed by applying the method in 200 display film samples. As a result, the detection rate was high at about 95.5%. Moreover, the study was able to acquire reliable results using the Semu index for luminance mura in image quality inspection.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11A
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• pp.1190-1196
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• 2007

In this paper, we propose the biometrics system using hand vein pattern. This system is for management about person's entrance/exit in vessel USN. we select the biometrics method using hand vein pattern as adoptable method to vessel USN environment. Our experimental results show that preprocessing using two dimensional gabor filter achieves performance improvements over high pass filtering. Also, we compared our method with measured FAR(False Acceptance Rate) and FRR(False Rejection Rate) using pattern matching, the results show low error rate over high pass filtering. As a result, we verify the adoptability of biometrics system using hand vein pattern in management of person's entrance/exit in vessel.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.33-36
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• 2001

We introduce, in this paper, the face recognition method that improves recognition rate and training time in eigen system. To increase recognition rate we use Gabor filter. To reduce the increasing training time owing to use Gabor filtering, we extract new feature vectors that are made with average and standard deviation. In experimental results, we get higher recognition rate and shorter training time in improved system than it in original eigen system.

• Journal of Industrial Technology
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• v.28 no.B
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• pp.143-148
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• 2008

A real-time face detection is to find human faces robustly under the cluttered background free from the effect of occlusion by other objects or various lightening conditions. We propose a face detection system for real-time applications using wavelet decomposition method based on Gabor features. Firstly, skin candidate regions are extracted from the given image by skin color filtering and projection method. Then Gabor-feature based template matching is performed to choose face cadidate from the skin candidate regions. The chosen face candidate region is transformed into 2-level wavelet decomposition images, from which feature vectors are extracted for classification. Based on the extracted feature vectors, the face candidate region is finally classified into either face or nonface class by the Levenberg-Marguardt back-propagation neural network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11C
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• pp.1510-1517
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• 2004

A new fingerprint image enhancement algorithm using multiresolution information and Gabor filter is proposed in this paper. The proposed algorithm performs selection of the region in image according to inclusion of singular points and then performs enhancement using Gabor filtering of the region adjusted in its size. Gabor filter using representative direction in the same block is used in the region that the direction of ridge is not changed much, while Gabor filter using pixel based direction is used in the region that the direction of ridge is changed much. This method can reduce processing time for enhancement using Gabor filter and preserve the merit of Gabor filter.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2032-2035
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• 2003

This paper focused on the possibility of face recognition using Flexible let Point Setting method in Gabor Filter Based Face Recognition. Gabor Filter is very sensible to the Texture variation. Therefore, any little change in the face expression or rotation of posture make recognition rate down significantly. A suggested solution for this problem is the Flexible Jet Point Setting. A significant effect of this method is that the number of Jet Point has been reduced from over 150 to under 30 even though the change of recognition rate between two methods is neglectable, Furthermore a set of feature values which results from a set of Gabor filtering became insensible to face variation such as expression, rotation, and light effect. Retinex Algorithm which has been developed by NASA are used as pre-processing.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.653-662
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• 2002

Fingerprint recognition is a task to find a matching pattern in a database for a specific persons fingerprint. To accomplish this task, preprocessing, classification, and matching steps are taken for a large-scale fingerprint database but only the matching step is taken without classification for a small-scale database. The primary matching method is based on minutiae (ridge ending point, bifurcation). This matching method, however, requires a very complex computation to extract minutiae and match minutiae-to-minutiae accurately due to translation, rotation, nonlinear deformation of fingerprint and occurrence of spurious minutiae. In addition, this method requires a laborious preprocessing step in order to improve the quality of fingerprint Images. This paper proposes a new simple method to eliminate these problems. With this method, Gabor variance is used instead of minutiae for fingerprint recognition. The Gabor variance is computed from Gabor features that result from filtering a fingerprint image through Gabor filter. In this paper, this method is described and its test result is shown, demonstrating the potential of using this new method for fingerprint recognition.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.1-8
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• 2010

Noise removal methods for noisy images have been studied a lot in the domain of spatial and transform filtering. Low pass filtering was initially applied in the spatial domain. Recently, discrete wavelet transform has widely used for image denoising as well as image compression due to an excellent energy compaction and a property of multiresolution. In this paper, Gabor cosine and sine transform which is considered as human visual filter is applied to image denoising areas using soft thresholding technique. GCST is compared with excellent wavelet transform which uses existing soft thresholding methods from PSNR point of view. Resultant images removed noises are also visually compared. Experimental results with adding four different standard deviation levels of Gaussian distributed noises to real images show that the proposed transform has better PSNR performance of a maximum of 1.18 dB and visible perception than wavelet transform.