• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.525-534
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• 2013

Recently, mura defect inspection techniques are receiving attention in LCD production procedure since demands of TFT-LCD are growing. In this paper, we propose an automatic mura defect inspection method using gabor wavelet transform and DCT. First, we generate a reference panel image using DCT based method. For original panel image and generated reference panel image, we apply a gabor wavelet transform to eliminate texture information in images. Then, we extract mura defect regions from the difference image between gabor wavelet transform image of original panel and generated reference panel image. Finally, all mura defect regions are quantified to detect accurate mura defects. Experimental results show that our method is more accurate and efficient than previous methods.

• Journal of Korea Multimedia Society
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• v.10 no.9
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• pp.1125-1134
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• 2007

In this paper, we propose a new approach for rotation invariant texture classification based on Gabor wavelet. Conventional methods have the low correct classification rate in large texture database. In our proposed method, we define two feature groups which are the global feature vector and the local feature matrix. The feature groups are output of Gabor wavelet filtering. By using the feature groups, we defined an improved discriminant and obtained high classification rates of large texture database in the experiments. From spectrum symmetry of texture images, the number of test times were reduced nearly 50%. Consequently, the correct classification rate is improved with $2.3%{\sim}15.6%$ values in 112 Brodatz texture class, which may vary according to comparison methods.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.215-218
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• 2000

This paper describes a new algorithm for segmenting continuous handwritten signatures sampled by a digitizer. Signatures are segmented by three procedures. The first step is to calculate the pen tip speed. Then the Gabor wavelet is carried out on the acquired data from the first step. Finally, the local minima of the filtered output are selected as segmentation points of the signature. The proposed method is experimented with numerous signatures with various length and complexity.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2020-2023
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• 2003

In this paper, our proposed system uses the regional Gabor wavelet and Neural Network to implement face recognition similar to human face recognition system, because the Gator wavelet expresses visual recognition system of human mathematically and the regional Neural Network is robust to white noise and partial illumination. This system consists of two stages of building database and recognizing face. One is composed by using the supervised learning of Neural Network. At this time, the Neural Network is applied to the upper and the lower part of face images respectively. The Backpropagation algorithm is used to learn Neural Network. Another consists of calibration of slope of face image, measurement of illumination variant using deviation with average face image and similarity comparison using Euclidean distance measure.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.81-88
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• 2004

In this paper, we propose a new objective quality assessment method considering the human visual perception characteristics. A subjective quality assessment is obtained by the response of the receptive field in the primary visual cortex and a human's eye can't focus on all of the visual range in a moment. Take advantage of two facts above, we apply Gabor wavelet transform which is well fit the receptive field in the cortex, to divided constant sized subblocks. Then a local distortion of the subblocks and a global distortion for the entire image are calculated in order. The proposed method has been evaluated using video test sequences provided by the Video Quality Experts Group (VQEG). The experimental results show that good correlation with human perception is obtained using the proposed metric, which is what we called GPSNR.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.126-132
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• 2000

This paper presents a facial expression recognition based on Gabor wavelets that uses a fuzzy C-means(FCM) clustering algorithm and neural network. Features of facial expressions are extracted to two steps. In the first step, Gabor wavelet representation can provide edges extraction of major face components using the average value of the image's 2-D Gabor wavelet coefficient histogram. In the next step, we extract sparse features of facial expressions from the extracted edge information using FCM clustering algorithm. The result of facial expression recognition is compared with dimensional values of internal stated derived from semantic ratings of words related to emotion. The dimensional model can recognize not only six facial expressions related to Ekman's basic emotions, but also expressions of various internal states.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.7
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• pp.323-326
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• 2002

As multimedia database and digital image libraries are enlarged, CBIR(Content Based Image Retrieval) has been getting importance for the efficient search. Generally, CBIR uses primitive features such as color, shape, texture and so on. Among various methods of CBIR, Gabor wavelet has good image retrieval performance with texture features but it has a disadvantage which does not perform well for a rotated image because of its direction oriented filter. In this paper, we propose a new method to solve this problem by modifying Gabor filter for all directions. And then we will compare the searching performance of the proposed method with those of conventional image retrieval methods through experiments with trademarks.

• Proceedings of the Safety Management and Science Conference
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• 2001.11a
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• pp.91-97
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• 2001

본 연구는 Fourier, Shannon, Gabor, Wavelet Filters 간의 상호비교를 통해 Wavelet Analysis의 장점을 도출하고 학제간 모든 과학기술에 적용될 수 있는 분야를 유형화하고 기존 연구를 고찰한다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.10 s.113
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• pp.913-919
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• 2006

This paper presents a technique for motion compensation of ISAR(Inverse SAR) images for a moving target. If a simple fourier transform is employed to obtain ISAR image for a moving target, the image is usually blurred. These images blurring problem can be solved with the time-frequency transform. In this paper, motion compensation algorithms of ISAR image such as STFT(Short Time Fourier Transform), GWT(Gabor Wavelet Transform) are described. In order to show the performances of each algorithm, we use scattering wave of the ideal point scatterers and simulated MIG-25 to obtain motion compensated ISAR image, and display the resolution of STFT and GWT ISAR image.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1372-1381
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• 2017

In this paper, a texture feature extraction method using local energy and local correlation of Gabor transformed images is proposed and applied to an image retrieval system. The Gabor wavelet is known to be similar to the response of the human visual system. The outputs of the Gabor transformation are robust to variants of object size and illumination. Due to such advantages, it has been actively studied in various fields such as image retrieval, classification, analysis, etc. In this paper, in order to fully exploit the superior aspects of Gabor wavelet, local energy and local correlation features are extracted from Gabor transformed images and then applied to an image retrieval system. Some experiments are conducted to compare the performance of the proposed method with those of the conventional Gabor method and the popular rotation-invariant uniform local binary pattern (RULBP) method in terms of precision vs recall. The Mahalanobis distance is used to measure the similarity between a query image and a database (DB) image. Experimental results for Corel DB and VisTex DB show that the proposed method is superior to the conventional Gabor method. The proposed method also yields precision and recall 6.58% and 3.66% higher on average in Corel DB, respectively, and 4.87% and 3.37% higher on average in VisTex DB, respectively, than the popular RULBP method.