• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.3
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• pp.11-22
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• 2002

The design of optimal filter yielding optimal texture feature separation is a most effective technique in many torture analyzing areas, such as perception of surface, object, shape and depth. But, most optimal filter design approaches are restricted to the issue of computational complexity and supervised problems. In this paper, Our proposed method yields new insight into the design of optimal Gabor filters for segmenting multiple texture images. The optimal frequency of Gator filter is turned to the optimal frequency of the distinct texture in frequency domain. In order to show the performance of the designed filters, we have attempted to build a various texture images. Our experimental results show that the performance of the system is very successful.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.1-7
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• 2004

For the handwritten digit recognition, this paper Proposes a hierarchical Gator features extraction method and a Bayesian network for them. Proposed Gator features are able to represent hierarchically different level information and Bayesian network is constructed to represent hierarchically structured dependencies among these Gator features. In order to extract such features, we define Gabor filters level by level and choose optimal Gabor filters by using Fisher's Linear Discriminant measure. Hierarchical Gator features are extracted by optimal Gabor filters and represent more localized information in the lower level. Proposed methods were successfully applied to handwritten digit recognition with well-known naive Bayesian classifier, k-nearest neighbor classifier. and backpropagation neural network and showed good performance.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.433-436
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• 2001

본 논문에서는, 지문인식에 있어서 특징 추출알고리즘과 추출된 특징을 가지고, matching하는 알고리즘을 제안하였다. 지문인식에 필요한 특징추출 알고리즘들은 Gabor-filter라는 알고리즘에 기반을 두었으며, minutiae 와는 달리 특징추출에 있어서 전처리과정(smoothing, binarization, thining, restoration) 을 필요로 하지않는다. 또한, 지문의 matching에 있어서의 알고리즘은 fingercode들 간의 유사성에 기반을 두었다. 이를 통한 실 험결과로써, 인식의 정확성은 95.7(%), FAR(2.9%), FRR(1.4%)을 보여주었다.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.133-136
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• 2002

In this paper, we propose a method to extract vertical stripes projected on human face using Gabor filter, Previous work cannot extract continuous vertical stripes in the eye and mouth region due to their horizontal lines, Proposed method use Gator filter adaptively according to main frequencies and directions of stripes in each block. Experimental results show that Proposed method can extract continuous vertical stripes in the eye and mouth region

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.87-94
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• 2008

In this paper, an extraction method of objects of interest in the color images is proposed. It is possible to extract objects of interest from a complex background without any prior-knowledge based on the proposed method. For object extraction, Gator images that contain information of object location, are created by using Gator filter. Based on the images the initial location of attention windows is determined, from which image features are selected to extract objects. To extract object, I modify the previous method partially and apply the modified method. To evaluate the performance of propsed method, precision, recall and F-measure are calculated between the extraction results from propsed method and manually extracted results. I verify the performance of the proposed methods based on these accuracies. Also through comparison of the results with the existing method, I verily the superiority of the proposed method over the existing method.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2595-2597
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• 2002

오늘날 많은 디지털 저장 매체의 발달로 방대한 양의 영상 데이터가 데이터베이스화 되고 있으며 이러한 데이터베이스에서 필요한 영상 데이터론 효율적으로 검색하는 방범이 중요한 문제로 대두되고 있다. 현재 영상의 색상, 형태 및 질감 특성을 사용하여 다양한 영상 검색 방법이 제안되고 있으며 본 연구에선 이중 질감을 특징으로 하는 Gator 특징 벡터를 사용하고자 한다. 즉, 영상의 인터레스트 포인트를 찾아내어 그 점에서 Gabor 웨이블릿을 이용하여 특징 벡터를 추출하고 VQ를 기반으로 한 히스토그램 인터섹션 방법을 이용하여 영상 검색을 한다. 기존의 Gator 웨이블릿 방법은 영상의 회전에 대해 잘 동작하지 못하는 단점을 가지고 있으며 이는 회전 영상에 대한 검색율 저하에 크게 작용한다. 이 문제를 해결하고자 본 논문에선 회전 불변 Gabor 필터를 이용한 영상 검색 방법을 제안하고자 한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.103-113
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• 2003

We must enhance a fingerprint image to improve the performance of a fingerprint recognition. Because of this reason, many researches were achieved about the fingerprint image enhancement. Representative method is to use Gabor-Filter among them. However GF has the weakness which a processing hour takes long. In this paper, we proposed Half Gabor Filter (HGF) to enhance the fingerprint image fast in the on-line. The HGF, however, can make calculation much simpler, as well as both minutiae-extraction rate and recognition rate. On the other hand, the fingerprint image to enhance using HGF has almost same with the case effectiveness to apply GF. In this paper, we confirme it mathematically and experimentally.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.321-324
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• 2002

In this paper, we introduce a new approach to fingerprint classification based on both singular points and gabor features. We find singular points of fingerprint image by using squared direction field and Poincare index. Then, the input fingerprint image can be classified into one of 5 classes using the number of singular points and their location. However, it is often impossible to classify the fingerprint image because the numbers and the position of the singular points are not correct due to noise. In this case Gabor features are extracted from unclassified images using Gator filter and they are classified by using k-NN classifier. This method has been tested on the NIST-4 database. The experimental results show that the proposed method is reliable.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.70-76
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• 2002

In this paper, we proposed a personal identification algorithm using the iris region which has discriminant features. First, we acquired the eye image with the black and white CCD camera and extracted the iris region by using a circular edge detector which minimizes the search space for real center and radius of the iris. And then, we localized the iris region into several circles and extracted the features by filtering signals on the perimeters of circles with one dimensional Gabor filter We identified a person by comparing ,correlation values of input signals with the registered signals. We also decided threshold value minimizing average error rate for FRR(Type I)error rate and FAR(Type II)error rate. Experimental results show that proposed algorithm has average error rate less than 5.2%.