• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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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".

• 방송공학회논문지
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• 제13권1호
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• pp.109-118
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• 2008

텍스처 영상 압축은 JPEG과 같은 영상 압축 표준을 사용한다. 일반 텍스처 영상에는 JPEG으로도 좋은 압축 성능을 내지만 패치 텍스처 영상은 이러한 영상 압축 기술로 압축했을 때 좋은 압축 성능을 보이지 못하였다. 이를 보완하고 압축 성능을 높이기 위해 기존의 패치 텍스처 영상에 주변 화소간에 색차를 줄이기 위한 전처리 기술을 소개하고, 제안된 기술과 JPEG 압축을 순서대로 적용하였을 때 압축 성능이 23%에서 45%까지 향상됨을 보이고자 한다.

• 제어로봇시스템학회논문지
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• 제8권6호
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• pp.455-461
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• 2002

Object-based image retrieval method is addressed. A new image segmentation algorithm and image comparing method between segmented objects are proposed. For image segmentation, color and texture features are extracted from each pixel in the image. These features we used as inputs into VQ (Vector Quantization) clustering method, which yields homogeneous objects in terns of color and texture. In this procedure, colors are quantized into a few dominant colors for simple representation and efficient retrieval. In retrieval case, two comparing schemes are proposed. Comparing between one query object and multi objects of a database image and comparing between multi query objects and multi objects of a database image are proposed. For fast retrieval, dominant object colors are key-indexed into database.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권10호
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• pp.5197-5218
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• 2019

Large-scale retrieval algorithm is problem for visual analyses applications, along its research track. In this paper, we propose a high-efficiency region division-based image retrieve approaches, which fuse low-level local color histogram feature and texture feature. A novel image region division is proposed to roughly mimic the location distribution of image color and deal with the color histogram failing to describe spatial information. Furthermore, for optimizing our region division retrieval method, an image descriptor combining local color histogram and Gabor texture features with reduced feature dimensions are developed. Moreover, we propose an extended Canberra distance method for images similarity measure to increase the fault-tolerant ability of the whole large-scale image retrieval. Extensive experimental results on several benchmark image retrieval databases validate the superiority of the proposed approaches over many recently proposed color-histogram-based and texture-feature-based algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권7호
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• pp.2400-2419
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• 2014

Pre-segmented pixels can reduce the difficulty of segmentation and promote the segmentation performance. This paper proposes a novel segmentation method based on merging texture superpixels by computing inner similarity. Firstly, we design a set of Gabor filters to compute the amplitude responses of original image and compute the texture map by a salience model. Secondly, we employ the simple clustering to extract superpixles by affinity of color, coordinates and texture map. Then, we design a normalized histograms descriptor for superpixels integrated color and texture information of inner pixels. To obtain the final segmentation result, all adjacent superpixels are merged by the homogeneity comparison of normalized color-texture features until the stop criteria is satisfied. The experiments are conducted on natural scene images and synthesis texture images demonstrate that the proposed segmentation algorithm can achieve ideal segmentation on complex texture regions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3642-3667
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• 2021

Texture synthesis technology has the advantages of repairing texture and structure at the same time. However, during the filling process, the size of the patch is fixed, and the content of the filling is not fully considered. In order to be able to adaptively change the patch size, we used the exemplar-based inpainting technique as the test algorithm, considering the image structure and texture, calculated the image structure patch size and texture patch size, and comprehensively determined the image patch size. This can adaptively change the patch size according to the filling content. In addition, we use multi-layer images to calculate the priority, so that the order of image repair was more stable. The proposed repair algorithm is compared with other image repair algorithms. The experimental results showed that the proposed adaptive image repair algorithm can better repair the texture and structure of the image, which proved the effectiveness of the proposed algorithm.

• 한국컴퓨터정보학회논문지
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• 제21권11호
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• pp.17-21
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• 2016

Heterogeneity assessment of tumor in oncology is important for diagnosis of cancer and therapy. The aim of this study was performed assess heterogeneity tumor region in PET image using texture analysis. For assessment of heterogeneity tumor in PET image, we inserted sphere phantom in torso phantom. Cu-64 labeled radioisotope was administrated by 156.84 MBq in torso phantom. PET/CT image was acquired by PET/CT scanner (Discovery 710, GE Healthcare, Milwaukee, WI). The texture analysis of PET images was calculated using occurrence probability of gray level co-occurrence matrix. Energy and entropy is one of results of texture analysis. We performed the texture analysis in tumor, liver, and background. Assessment textural features of region-of-interest (ROI) in torso phantom used in-house software. We calculated the textural features of torso phantom in PET image using texture analysis. Calculated entropy in tumor, liver, and background were 5.322, 7.639, and 7.818. The further study will perform assessment of heterogeneity using clinical tumor PET image.

• 정보처리학회논문지B
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• 제9B권3호
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• pp.327-336
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• 2002

텍스쳐 분석은 표면, 물체, 모양, 깊이 인식 등의 많은 영상 이해 분야에서 활용되는 가장 중요한 인식 기술 중의 하나이다. 그러나 기존의 방법들은 다중 텍스쳐 영상에 내재된 텍스쳐 성분의 인식 정보를 활용할 수 없는 분할만을 목적으로 하고 있으며, 내재된 텍스쳐 인식을 기반으로 하는 비교사적인 방법에 관한 연구는 거의 이루어지고 있지 않은 실정이다. 따라서 본 논문에서는 텍스쳐 성분을 방향장(orientation-field) 특징 정보인 방향각과 방향강도로 정의하고 블록-기반 자기조직화 신경회로망에 의해서 비교사적으로 영상 내에 존재하는 텍스쳐 영역을 군화(clustering) 및 통합(merging) 처리에 의해서 식별한다. 또한 제안된 알고리즘의 성능 평가를 위해서는 다양한 형태의 다중 텍스쳐 영상을 생성하여 블록 기반의 불림(dilation) 및 윤곽 검출 과정을 통해서 영상에 내재하는 텍스쳐 영역을 분할함으로써 그 유효성을 보인다.

• 대한전자공학회논문지
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• 제26권9호
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• pp.1428-1435
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• 1989

In this paper we propose a new algorithm which extracts spatial arrangement information of texture elements in structural textures. In the proposed algorithm, by the use of projection information in several directions obtained from the texture image we can get two directions which determine the texture structure and the parallelogram grid which isolates texture elements. The isolated texture elements are analyzed and used to synthesize texture images. Computer simulation shows that the proposed method can extract proper spatial structure of the texture element even when the texture image is highly corrupted by additive noise.

• 대한원격탐사학회지
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• 제21권3호
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• pp.243-252
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• 2005

Wavelet transform and its inverse processing provide the effective framework for data fusion. The purpose of this study is to investigate applicability of wavelet transform using texture images for the urban remote sensing application. We tried several experiments regarding image fusion by wavelet transform and texture imaging using high resolution images such as IKONOS and KOMPSAT EOC. As for texture images, we used homogeneity and ASM (Angular Second Moment) images according that these two types of texture images reveal detailed information of complex features of urban environment well. To find out the useful combination scheme for further applications, we performed DWT(Discrete Wavelet Transform) and IDWT(Inverse Discrete Wavelet Transform) using texture images and original images, with adding edge information on the fused images to display texture-wavelet information within edge boundaries. The edge images were obtained by the LoG (Laplacian of Gaussian) processing of original image. As the qualitative result by the visual interpretation of these experiments, the resultant image by each fusion scheme will be utilized to extract unique details of surface characterization on urban features around edge boundaries.