• Title/Summary/Keyword: texture extraction

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A Fast and Adaptive Feature Extraction Method for Textured Image Segmentation (Texture 영상 분할을 위한 고속 적응 특징 추출 방법)

  • 이정환;김성대
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.16 no.12
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    • pp.1249-1265
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    • 1991
  • In this paper, a fast and adaptive feature extraction algorithm for textured image segmentation is proposed. First, a conventional algorithm to extract the statistical texture features are described and we obtain the recursive equations from that conventional method and it is used for extraction of sevaral texture features. And also we propose the adaptive algorithm which extract the texture features. To evaluate the performance of proposed algorithm, we apply the proposed method to artificial texture images. From the results of computer simulation, the proposed method is superior to the conventional one.

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Hybrid Approach of Texture and Connected Component Methods for Text Extraction in Complex Images (복잡한 영상 내의 문자영역 추출을 위한 텍스춰와 연결성분 방법의 결합)

  • 정기철
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.6
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    • pp.175-186
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    • 2004
  • We present a hybrid approach of texture-based method and connected component (CC)-based method for text extraction in complex images. Two primary methods, which are mainly utilized in this area, are sequentially merged for compensating for their weak points. An automatically constructed MLP-based texture classifier can increase recall rates for complex images with small amount of user intervention and without explicit feature extraction. CC-based filtering based on the shape information using NMF enhances the precision rate without affecting overall performance. As a result, a combination of texture and CC-based methods leads to not only robust but also efficient text extraction. We also enhance the processing speed by adopting appropriate region marking methods for each input image category.

Evaluation of Volumetric Texture Features for Computerized Cell Nuclei Grading

  • Kim, Tae-Yun;Choi, Hyun-Ju;Choi, Heung-Kook
    • Journal of Korea Multimedia Society
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    • v.11 no.12
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    • pp.1635-1648
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    • 2008
  • The extraction of important features in cancer cell image analysis is a key process in grading renal cell carcinoma. In this study, we applied three-dimensional (3D) texture feature extraction methods to cell nuclei images and evaluated the validity of them for computerized cell nuclei grading. Individual images of 2,423 cell nuclei were extracted from 80 renal cell carcinomas (RCCs) using confocal laser scanning microscopy (CLSM). First, we applied the 3D texture mapping method to render the volume of entire tissue sections. Then, we determined the chromatin texture quantitatively by calculating 3D gray-level co-occurrence matrices (3D GLCM) and 3D run length matrices (3D GLRLM). Finally, to demonstrate the suitability of 3D texture features for grading, we performed a discriminant analysis. In addition, we conducted a principal component analysis to obtain optimized texture features. Automatic grading of cell nuclei using 3D texture features had an accuracy of 78.30%. Combining 3D textural and 3D morphological features improved the accuracy to 82.19%. As a comparative study, we also performed a stepwise feature selection. Using the 4 optimized features, we could obtain more improved accuracy of 84.32%. Three dimensional texture features have potential for use as fundamental elements in developing a new nuclear grading system with accurate diagnosis and predicting prognosis.

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AUTOMATIC TEXTURE EXTRACTION FROM AERIAL PHOTOGRAPHS USING THE ZI-BUFFER

  • Han, Dong-Yeob;Kim, Yong-Il;Yu, Ki-Yun;Lee, Hyo-Seong;Park, Byoung-Uk
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.584-586
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    • 2007
  • 3D virtual modeling such as creation of a cyber city or landscape, or making a 3D GIS requires realistic textures. Automatic texture extraction using close range images is not yet efficient or easy in terms of data acquisition and processing. In this paper, common problems associated with automatic texture extraction from aerial photographs are explored. The ZI-buffer, which has depth and facet ID fields, is proposed to remove hidden pixels. The ZI-buffer algorithm reduces memory burden and identifies visible facets. The correct spatial resolution for facet gridding is tested. Error pixels in the visibility map were removed by filtering.

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A Study on Efficient FPS Game Operation Using Attention NPC Extraction (관심 NPC 추출을 이용한 효율적인 FPS 게임 운영에 관한 연구)

  • Park, Changmin
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.13 no.2
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    • pp.63-69
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    • 2017
  • The extraction of attention NPC in a FPS game has emerged as a very significant issue. We propose an efficient FPS game operation method, using the attention NPC extraction with a simple arithmetic. First, we define the NPC, using the color histogram interaction and texture similarity in the block to determine the attention NPC. Next, we use the histogram of movement distribution and frequency of movement of the NPC. Becasue, except for the block boundary according to the texture and to extract only the boundaries of the object block. The edge strength is defined to have high values at the NPC object boundaries, while it is designed to have relatively low values at the NPC texture boundaries or in interior of a region. The region merging method also adopts the color histogram intersection technique in order to use color distribution in each region. Through the experiment, we confirmed that NPC has played a crucial role in the FPS game and as a result it draws more speed and strategic actions in the game.

Development of Digital Surface Model and Feature Extraction by Integrating Laser Scanner and CCD sensor

  • Nagai, Masahiko;Shibasaki, Ryosuke;Zhao, Huijing;Manandhar, Dinesh
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.859-861
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    • 2003
  • In order to present a space in details, it is indispensable to acquire 3D shape and texture simultaneously from the same platform. 3D shape is acquired by Laser Scanner as point cloud data, and texture is acquired by CCD sensor. Positioning data is acquired by IMU (Inertial Measurement Unit). All the sensors and equipments are assembled on a hand-trolley. In this research, a method of integrating the 3D shape and texture for automated construction of Digital Surface Model is developed. This Digital Surface Model is applied for efficient feature extraction. More detailed extraction is possible , because 3D Digital Surface Model has both 3D shape and texture information.

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Design and Implementation of Virtual Aquarium

  • Bak, Seon-Hui;Lee, Heeman
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.12
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    • pp.43-49
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    • 2016
  • This paper presents the design and implementation of virtual aquarium by generating 3D models of fishes that are colored by viewers in an aim to create interaction among viewers and aquarium. The virtual aquarium system is composed of multiple texture extraction modules, a single interface module and a single display module. The texture extraction module recognize the QR code on the canvas to get information of the predefined mapping table and then extract the texture data for the corresponding 3D model. The scanned image is segmented and warp transformed onto the texture image by using the mapping information. The extracted texture is transferred to the interface module to save on the server computer and the interface module sends the fish code and texture information to the display module. The display module generates a fish on the virtual aquarium by using predefined 3D model with the transmitted texture. The fishes on the virtual aquarium have three different swimming methods: self-swimming, autonomous swimming, and leader-following swimming. The three different swimming methods are discussed in this paper. The future study will be the implementation of virtual aquarium based on storytelling to further increase interactions with the viewer.

New Texture Recognition Method Using Local Weighting Averaged Texture Units (국부 가중평균 질감단위를 이용한 새로운 질감인식 기법)

  • ;;;Ruud M. Bolle
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.4
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    • pp.129-137
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    • 1994
  • In this paper, a new texture feature extraction method for texture image classification is proposed. The proposed method is a modified texture spectrum method. It uses local weighting averaged texture unit, that is, the neighbor pixels are weithted and averaged in 4-direction and the calculated values are compared with center pixel to find texture units. The proposed method has only 81 texture units and these units are really good features for texture classification. The proposed method is applied to vegetable images and Blodatz album images and compared with several conventional methods for the feature extraction time and the recognition rate.

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Automatic Extraction of Rescue Requests from Drone Images: Focused on Urban Area Images (드론영상에서 구조요청자 자동추출 방안: 도심지역 촬영영상을 중심으로)

  • Park, Changmin
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.15 no.3
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    • pp.37-44
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    • 2019
  • In this study, we propose the automatic extraction method of Rescue Requests from Drone Images. A central object is extracted from each image by using central object extraction method[7] before classification. A central object in an images are defined as a set of regions that is lined around center of the image and has significant texture distribution against its surrounding. In this case of artificial objects, edge of straight line is often found, and texture is regular and directive. However, natural object's case is not. Such characteristics are extracted using Edge direction histogram energy and texture Gabor energy. The Edge direction histogram energy calculated based on the direction of only non-circular edges. The texture Gabor energy is calculated based on the 24-dimension Gebor filter bank. Maximum and minimum energy along direction in Gabor filter dictionary is selected. Finally, the extracted rescue requestor object areas using the dominant features of the objects. Through experiments, we obtain accuracy of more than 75% for extraction method using each features.

Efficient Content-Based Image Retrieval Methods Using Color and Texture

  • Lee, Sang-Mi;Bae, Hee-Jung;Jung, Sung-Hwan
    • ETRI Journal
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    • v.20 no.3
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    • pp.272-283
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    • 1998
  • In this paper, we propose efficient content-based image retrieval methods using the automatic extraction of the low-level visual features as image content. Two new feature extraction methods are presented. The first one os an advanced color feature extraction derived from the modification of Stricker's method. The second one is a texture feature extraction using some DCT coefficients which represent some dominant directions and gray level variations of the image. In the experiment with an image database of 200 natural images, the proposed methods show higher performance than other methods. They can be combined into an efficient hierarchical retrieval method.

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