| 书目名称 | Statistical Models of Shape | | 副标题 | Optimisation and Eva | | 编辑 | Chris Taylor,Carole Twining,Rhodri Davies | | 视频video | | | 概述 | Addresses one of the key issues in shape modelling: that of establishing a meaningful correspondence between a set of shapes.Uses a novel approach to establishing correspondence by casting model-build | | 图书封面 |  | | 描述 | The goal of image interpretation is to convert raw image data into me- ingful information. Images are often interpreted manually. In medicine, for example, a radiologist looks at a medical image, interprets it, and tra- lates the data into a clinically useful form. Manual image interpretation is, however, a time-consuming, error-prone, and subjective process that often requires specialist knowledge. Automated methods that promise fast and - jective image interpretation have therefore stirred up much interest and have become a signi?cant area of research activity. Early work on automated interpretation used low-level operations such as edge detection and region growing to label objects in images. These can p- ducereasonableresultsonsimpleimages,butthepresenceofnoise,occlusion, andstructuralcomplexity oftenleadstoerroneouslabelling. Furthermore,- belling an object is often only the ?rst step of the interpretation process. In order to perform higher-level analysis, a priori information must be incor- rated into the interpretation process. A convenient way of achieving this is to use a ?exible model to encode information such as the expected size, shape, appearance, and position of obj | | 出版日期 | Book 2008 | | 关键词 | Computer Vision; Computer visison; Correspondence; Medical image analysis; Minimum description length; Pa | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-84800-138-1 | | isbn_softcover | 978-1-4471-6042-7 | | isbn_ebook | 978-1-84800-138-1 | | copyright | Springer-Verlag London 2008 |
The information of publication is updating
|
|
发表于 2025-3-21 19:48:49
