• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.421-428
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• 2004

There are three texture descriptors in MPEG-7 : Homogeneous Texture, Edge Histogram and Texture Browsing. In this paper, a comparative analysis is presented on the capability of MPEG-7 texture descriptors for iris recognition as part of an MPEG-7 application using descriptors. Through the experiments of comparing the clustering efficiency and error distribution of the descriptors using 560 iris images, their discriminating capabilities for different iris groups are analyzed. The results show that Homogenous Texture descriptor is the best discriminator among three descriptors to recognize the iris pattern. However, compared with the conventional iris recognition methods, it needs more efforts to enhance the results.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.807-810
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• 2003

This research uses high-resolution satellite images as a source of collecting farmland information. For effectively extract the paddy area, we use texture information and different classify methods to assist the satellite image classification. First, using maximum likelihood classifier to extract paddy information from images. The results show that User Accuracy and Procedure Accuracy of the paddy area can increase from 80.60% to 95.45% and 84.38% to 95.45%. Second, establishing a paddy Knowledge Base and using Knowledge Base Classifier to extract paddy area, and result shows the User Accuracy and Producer Accuracy to be 92.16% and 90.06%. Finally, The result shows we can effectively contribute to the paddy field information extraction from high-resolution satellite images.

• Journal of Computing Science and Engineering
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• v.10 no.2
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• pp.68-73
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• 2016

An efficient texture compression method is proposed based on a block matching process between the current block and the previously encoded blocks. Texture mapping is widely used to improve the quality of rendering results in real-time applications. For fast texture mapping, it is important to find an optimal trade-off between compression efficiency and computational complexity. Low-complexity methods (e.g., ETC1 and DXT1) have often been adopted in real-time rendering applications because conventional compression methods (e.g., JPEG) achieve a high compression ratio at the cost of high complexity. We propose a block matching-based compression method that can achieve a higher compression ratio than ETC1 and DXT1 while maintaining computational complexity lower than that of JPEG. Through a comparison between the proposed method and existing compression methods, we confirm our expectations on the performance of the proposed method.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.45-48
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• 2002

In this paper, we propose an iris recognition system using Homogeneous Texture descriptor of MPEG-7 standard. The texture of iris is generally used in iris recognition system. We segment the pupil with Hough transform and the boundary of iris with it's gray level difference between the white of the eye. To extract Homogeneous Texture descriptor, this iris image is transformed into polar coordinates. The extracted descriptor is then compared with the reference in DB. If their distance is larger than threshold, they are recognized as different iris. Test results will show that Homogeneous Texture descriptor can be a good measure for iris recognition system.

• 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.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.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.4
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• pp.108-114
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• 2008

In this paper, we proposed robust blind watermarking algorithm using texture block coefficient based on discrete cosine transform(DCT). The proposed method embedded all of watermark signals into DC component of $8\times8$ block DCT in order to robust various external attack The texture block coefficient was composed absolute value of DCT coefficients. Experiment showed that the proposed method better than conventional methods in the invisibility and various attack such as dithering, cropping, and scaling.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.525-528
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• 2009

Recently, image classification has been an important task in various fields. Generally, the performance of image classification is not good without the adjustment of image features. Therefore, it is desired that the way of automatic feature extraction. In this paper, we propose an image classification method which adjusts image features automatically. We assume that texture features are useful in image classification tasks because natural images are composed of several types of texture. Thus, the classification accuracy rate is improved by using distribution of texture features. We obtain texture features by calculating image features from a current considering pixel and its neighborhood pixels. And we calculate image features from distribution of textures feature. Those image features are adjusted to image classification tasks using Genetic Algorithm. We apply proposed method to classifying images into "head" or "non-head" and "male" or "female".

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.431-433
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• 2007

In This paper, we present a texture clustering method to extract Container ISO code in complex images. First, we make texture informations using top-hat morphology from realtime images, and we cluster those informations using horizontal and vertical clustering method to extract text area. After extensive experiment, our method demonstrated superior performance against well-known techniques as texture and histogram method.