• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.311-320
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• 2003

The Optimal filter yielding optimal texture feature separation is a most effective technique for extracting the texture objects from multiple textures images. But, most optimal filter design approaches are restricted to the issue of supervised problems. No full-unsupervised method is based on the recognition of texture objects in image. We propose a novel approach that uses unsupervised learning schemes for efficient texture image analysis, and the band-pass feature of Gabor-filter is used for the optimal filter design. In our approach, the self-organizing neural network for multiple texture image identification is based on block-based clustering. The optimal frequency of Gabor-filter is turned to the optimal frequency of the distinct texture in frequency domain by analyzing the spatial frequency. In order to show the performance of the designed filters, after we have attempted to build a various texture images. The texture objects extraction is achieved by using the designed Gabor-filter. Our experimental results show that the performance of the system is very successful.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.371-379
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• 2009

In this paper, we proposed new de-interlacing algorithm for video data using intensity gradient filter and median filter with texture detection in the image block. We first introduce the texture detection. According to texture detection, the current region is determined into smooth region or texture region. In case that the smooth region interpolated by median filter. In addition, in case of the texture region, we calculate missing pixel value using intensity gradient filter. Therefore, we analyze the local region feature using the texture detection and classify each missing pixel into two categories. And then, based on the classification result, a different de-interlacing algorithm is activated in order to obtain the best performance. Experimental results show that the proposed algorithm performs well with a variety of moving sequences compared with conventional intra-field method in the literature.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.1
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• pp.49-54
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• 2016

Regarding global and local factors of a set of features, a given single image or multiple images is a common approach in image processing. This paper introduces an application of an adaptive version of non-local filter whose original version searches non-local similarity for removing noise. Since most images involve texture partner in both foreground and background, extraction of signified regions with texture is a challenging task. Aiming to the detection of visual attention regions for images with texture, we present the contrast analysis of image patches located in a whole image but not nearby with assistance of the adaptive filter for estimation of non-local divergence. The method allows extraction of signified regions with texture of images of wild life. Experimental results for a benchmark demonstrate the ability of the proposed method to deal with the mentioned challenge.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.147-153
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• 2017

Efficient texture representation is very important in computer vision fields. The performance of texture classification or/and segmentation can be improved based on efficient texture representation. Gabor filter is a representation method that has long history for texture representation based on multi-scale analysis. Gabor filter shows good performance in texture classification and segmentation but requires much processing time. In this paper, we propose new texture representation method that is also based on multi-scale analysis. The proposed representation can provide similar performance in texture classification but can reduce processing time against Gabor filter. Experimental results show good performance of our method.

• Journal of IKEEE
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• v.5 no.2 s.9
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• pp.211-220
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• 2001

This paper proposes a 2-D texture segmentation algorithm which is in close analogy to amplitude demodulation in communication systems. First, we show that it is theoretically possible to segment a multitexture image using an ideal filter followed by an amplitude demodulation block. However, in practice, the Gabor filter is used instead of the ideal filter because it has many desirable properties and especially it gives optimum space-bandwidth product. Our algorithm recovers all the texture regions containing the sinusoid with frequency to which the Gabor filter is tuned. We have demonstrated the discriminating power of our method in using a synthetic multitexture image. It is clear mathematically and easy to implement. Our method can be a good alternative to avoid many problems encountered in classifying the feature vectors in feature-based texture segmentation approaches.

• Journal of Broadcast Engineering
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• v.20 no.5
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• pp.718-727
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• 2015

In this paper, we present a novel segmentation method that can extract new foreground objects from a current frame in real-time. It is performed by detecting differences between the current frame and reference frame taken from a fixed camera. We minimize computing complexity for real-time video processing. First DCT (Discrete Cosine Transform) is utilized to generate rough binary segmentation maps where foreground and background regions are separated. DCT shows better result of texture analysis than previous methods where texture analysis is performed in spatial domain. It is because texture analysis in frequency domain is easier than that in special domain and intensity and texture in DCT are taken into account at the same time. We maximize run-time efficiency of DCT by considering color information to analyze object region prior to DCT process. Last we use Guided filter for natural matting of the generated binary segmentation map. In general, Guided filter can enhance quality of intermediate result by incorporating guidance information. However, it shows some limitations in homogeneous area. Therefore, we present an additional method which can overcome them.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1123-1131
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• 1996

Several improved quadrature polar separable (QPS) filters have been proposed and applied in texture processing since Knutsson proposed the QPS filter. They include a Knutsson's cosine function or oan exponential attenuation function, as the orientational function, and a Knutsson's exponential function or a finite prolate spheroidal sequence (FPSS) or an asymptotic FPSS, as the radial weighting functions. They represent different properties in terms of the generation of texture images, the orientational estimation, and the segmentation of synthetic texture image. In this paper, we have constructed several kernal functions for the 2-D QPS filter and analyzed their properties. A series of experiments have been carried out in order to estimate the frequency components and orientational angles of a local texture in Fourier domain. finally some problems encountered in applying QPS filters to feature description and segmentation are considered. Experimental results show that the improved Knutsson's filter and the asymptotic FPSS filter are useful in terms of the orientational estimation and the sementation of synthetic texture image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.3
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• pp.288-296
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• 1992

This paper describes an improved 2D QPS(quadrature polar separable) filter design and its applications to texture processing. The filter kernel pair consists of the product of a radial weighting function based on the finite PSS (prolate spheroidal sequences) and an exponential at tenuation function for the orientational angle. It is quadrature and polar separable in the frequency domain. It is near optimal in the energy loss because we let the orientational angle function approximate the radial weighting function. The filter frequency characteristics is easy to control as it depends only upon the design specifications such as the bandwidth, the directional angle, the attenuation constant, and the shift constant of the central frequency. Some applications of the filter in texture processing, such as the generation of the texture image, the estimation of orientation angles, and the segmentations for the synthetic texture image, are considered. The result shows that the filter with the wide bandwidth can be used for the generation of discrimination of the strong orientational textures and the segmentation results are good.

• Korean Journal of Remote Sensing
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• v.18 no.3
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• pp.181-186
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• 2002

One of the most important procedure in stereo DEM generation is the stereo matching process which finds the conjugate pixels in a pair of stereo imagery. In order to be found as conjugate pixels, the pixels should have distinct spatial feature to be distinguished from other pixels. However, in the homogeneous areas such as water covered or forest canopied areas, it is very difficult to find the conjugate pixels due to the lack of distinct spatial feature. Most of erroneous elevation values in the stereo DEM are produced in those homogeneous areas. This paper presents a simple method for improving the quality of stereo DEM utilizing the texture filters. An entropy filter was applied to one of the input stereo imagery to extract very homogeneous areas before stereo matching process. Those extracted homogeneous areas were excluded from being candidates for stereo matching process. Also a statistical texture filter was applied to the generated elevation values before the interpolation process was applied in odor to remove the remaining anomalous elevation values. Stereo pair of SPOT level 1B panchromatic imagery were used for the experiments. The results showed that by utilizing the texture filters as a pre and a post processor of stereo matching process, the quality of the stereo DEM could be dramatically improved.