Nonlinear Radon Transform Using Zernike Moment for Shape Analysis
نویسندگان
چکیده
منابع مشابه
Nonlinear Radon Transform Using Zernike Moment for Shape Analysis
We extend the linear Radon transform to a nonlinear space and propose a method by applying the nonlinear Radon transform to Zernike moments to extract shape descriptors. These descriptors are obtained by computing Zernike moment on the radial and angular coordinates of the pattern image's nonlinear Radon matrix. Theoretical and experimental results validate the effectiveness and the robustness ...
متن کاملFacial Recognition using Hausdorff- Shape- Radon Transform
This paper proposes a robust method for face recognition with variant illumination, scaling and rotation. Techniques introduced in this work are composed of two stages. First, the feature of face is to be detected by the combined of Trace Transform and Fast Active Contour. Then, in the second stage, the Hausdorff distance and Modified Shape Context are employed to measure and determine of simil...
متن کاملVibration Mode Shape Recognition Using the Zernike Moment Descriptor
Vibration mode-shape comparison between numerical models and experimental data is an essential step in the study of structural finite element model (FEM) updating. The Modal Assurance Criterion (MAC) is the most popular method for such comparison at the moment, which works perfectly well for small and medium sized structures. MAC provides a measure of closeness between the predicted and measure...
متن کاملTexture Analysis Using Modified Discrete Radon Transform
In this paper, we address the problem of the rotationinvariant texture analysis. For this purpose, we first present a modified version of the discrete Radon transform whose performance, including accuracy and processing time, is significantly better than the conventional transform in direction estimation and categorization of textural images. We then utilize this transform with a rotated versio...
متن کاملContours Extraction Using Line Detection and Zernike Moment
Most of the contour detection methods suffers from some drawbacks such as noise, occlusion of objects, shifting, scaling and rotation of objects in image which they suppress the recognition accuracy. To solve the problem, this paper utilizes Zernike Moment (ZM) and Pseudo Zernike Moment (PZM) to extract object contour features in all situations such as rotation, scaling and shifting of object i...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computational and Mathematical Methods in Medicine
سال: 2013
ISSN: 1748-670X,1748-6718
DOI: 10.1155/2013/208402