Zernike moments and descriptors for 3D object processing

用于 3D 对象处理的 Zernike 矩和描述符

• 批准号: BB/F016220/1
• 负责人: Richard Morris
• 金额: $ 7.46万
• 依托单位: John Innes Centre
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2008
• 资助国家: 英国
• 起止时间: 2008 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FF016220%2F1
• 关键词: Zernike; moments; descriptors; 3D; object

A deeper understanding of mechanisms that underlie biological processes at the microscopic level, such as molecular recognition, requires models for describing three dimensional objects and how they interact. Similarly at the macroscopic level, shape and shape changes are a crucial first step in understanding growth and development. This has been recognised and biological imaging is enjoying an increased research effort worldwide and is providing stunning images and many new insights into important biological processes. A picture can say more than a thousand words. To store and index 3D images efficiently, a powerful shape description method is required. Plants represent highly challenging objects as they have convoluted forms that deviate significantly from so-called star-shape objects (which are computationally easier to handle). The underlying mathematical framework has been derived to allow many kinds of 3D shapes and distributions to be described by Zernike moments. With further development this approach can be made more efficient whilst including additional properties. The proposed research will build on the current proof-of-principle developments and translate them into robust code for efficiently comparing molecular shapes. Further enhancements to be investigated will include the extension of the current methodology to four dimensions, in which time is presented in the fourth coordinate. This will allow for shape changes (motion, deformation, growth) to be modeled within the same framework. In addition, reliable approaches for the segmentation of objects will be investigated. These developments will enable shapes to be assembled in space and missing components scanned for in shape databases. This enhancement will allow for flexible shape fitting, with applications in imaging, X-ray scattering and especially EM.

对微观水平生物学过程基础的机制（例如分子识别）的更深入的理解需要描述三维对象及其相互作用的模型。同样，在宏观水平上，形状和形状变化对于理解生长和发展也是至关重要的第一步。这已经得到认可，生物成像正在享受全球的研究工作，并为重要的生物学过程提供了令人惊叹的图像和许多新的见解。图片可以说一千多个单词。为了有效地存储和索引3D图像，需要一种强大的形状描述方法。植物代表着高度挑战的物体，因为它们的复杂形式与所谓的星形物体显着偏离（计算上更容易处理）。基本的数学框架已得出，以允许Zernike Moments描述多种3D形状和分布。随着进一步的发展，可以使这种方法更有效，同时包括其他属性。拟议的研究将基于当前的原理发展证明，并将其转化为强大的代码，以有效地比较分子形状。要研究的进一步增强功能将包括将当前方法扩展到四个维度，在第四个坐标中显示时间。这将使形状变化（运动，变形，生长）在同一框架内建模。此外，将研究可靠的对象分割方法。这些发展将使形状能够在空间中组装，并缺少用于形状数据库的组件。这种增强功能将允许柔性形状拟合，并在成像，X射线散射（尤其是EM）中进行应用。