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Titlebook: Computer Analysis of Visual Textures; Fumiaki Tomita,Saburo Tsuji Book 1990 Springer Science+Business Media New York 1990 Image segmentati

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發(fā)表于 2025-3-21 18:12:04 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Computer Analysis of Visual Textures
編輯Fumiaki Tomita,Saburo Tsuji
視頻videohttp://file.papertrans.cn/234/233458/233458.mp4
叢書(shū)名稱(chēng)The Springer International Series in Engineering and Computer Science
圖書(shū)封面Titlebook: Computer Analysis of Visual Textures;  Fumiaki Tomita,Saburo Tsuji Book 1990 Springer Science+Business Media New York 1990 Image segmentati
描述This book presents theories and techniques for perception of textures by computer. Texture is a homogeneous visual pattern that we perceive in surfaces of objects such as textiles, tree barks or stones. Texture analysis is one of the first important steps in computer vision since texture provides important cues to recognize real-world objects. A major part of the book is devoted to two-dimensional analysis of texture patterns by extracting statistical and structural features. It also deals with the shape-from-texture problem which addresses recovery of the three-dimensional surface shapes based on the geometry of projection of the surface texture to the image plane. Perception is still largely mysterious. Realizing a computer vision system that can work in the real world requires more research and ex- periment. Capability of textural perception is a key component. We hope this book will contribute to the advancement of computer vision toward robust, useful systems. vVe would like to express our appreciation to Professor Takeo Kanade at Carnegie Mellon University for his encouragement and help in writing this book; to the members of Computer Vision Section at Electrotechni- cal Labo
出版日期Book 1990
關(guān)鍵詞Image segmentation; Textur; cognition; computer; computer vision; object recognition; perception
版次1
doihttps://doi.org/10.1007/978-1-4613-1553-7
isbn_softcover978-1-4612-8832-9
isbn_ebook978-1-4613-1553-7Series ISSN 0893-3405
issn_series 0893-3405
copyrightSpringer Science+Business Media New York 1990
The information of publication is updating

書(shū)目名稱(chēng)Computer Analysis of Visual Textures影響因子(影響力)




書(shū)目名稱(chēng)Computer Analysis of Visual Textures影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Computer Analysis of Visual Textures網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Computer Analysis of Visual Textures網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Computer Analysis of Visual Textures被引頻次




書(shū)目名稱(chēng)Computer Analysis of Visual Textures被引頻次學(xué)科排名




書(shū)目名稱(chēng)Computer Analysis of Visual Textures年度引用




書(shū)目名稱(chēng)Computer Analysis of Visual Textures年度引用學(xué)科排名




書(shū)目名稱(chēng)Computer Analysis of Visual Textures讀者反饋




書(shū)目名稱(chēng)Computer Analysis of Visual Textures讀者反饋學(xué)科排名




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Computer Analysis of Visual Textures978-1-4613-1553-7Series ISSN 0893-3405
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發(fā)表于 2025-3-22 03:42:26 | 只看該作者
Renouvellement et existence de resolvantes,t textures is called .. Image segmentation is actually the first step of object recognition, because each region usually corresponds to one individual object, or each edge to the boundary between different objects. This chapter presents the algorithms for image segmentation.
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https://doi.org/10.1007/978-1-4613-1553-7Image segmentation; Textur; cognition; computer; computer vision; object recognition; perception
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978-1-4612-8832-9Springer Science+Business Media New York 1990
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Renouvellement et existence de resolvantes, a homogeneous visual pattern is called .. According to Pickett (1970),.Since any object has its own specific texture, human beings can use textures as cues to recognize many kinds of objects in the world. For example, we can identify the two textures in Figure 1.1 with straw and lawn. Even if we ca
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Renouvellement et existence de resolvantes,t textures is called .. Image segmentation is actually the first step of object recognition, because each region usually corresponds to one individual object, or each edge to the boundary between different objects. This chapter presents the algorithms for image segmentation.
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