Ring Image Analyzer software analyzes images to recognize elliptical patterns. It determines the ellipse parameters (axes ratio, centroid coordinate, tilt angle). The program attempts to recognize elliptical fringes (e.g., Newton Rings) on a photograph and determine their centroid position, the short-to-long-axis ratio, and the angle of rotation of the long axis relative to the horizontal direction on the photograph. These capabilities are important in interferometric imaging and control of surfaces. In particular, this program has been developed and applied for determining the rim shape of precisionmachined optical whispering gallery mode resonators.
The program relies on a unique image recognition algorithm aimed at recognizing elliptical shapes, but can be easily adapted to other geometric shapes. It is robust against non-elliptical details of the image and against noise.
Interferometric analysis of precisionmachined surfaces remains an important technological instrument in hardware development and quality analysis. This software automates and increases the accuracy of this technique. The software has been developed for the needs of an R&TD-funded project and has become an important asset for the future research proposal to NASA as well as other agencies.
This work was done by Dmitry V. Strekalov of Caltech for NASA’s Jet Propulsion Laboratory. This software is available for commercial licensing. Please contact Daniel Broderick of the California Institute of Technology at
This Brief includes a Technical Support Package (TSP).
Ring Image Analyzer
(reference NPO-47579) is currently available for download from the TSP library.
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Overview
The document is a Technical Support Package for the Ring Image Analyzer, developed by the Jet Propulsion Laboratory (JPL) at the California Institute of Technology. This program is designed to analyze photographs of elliptical fringes, such as Newton Rings, to determine key parameters including the centroid position, the short to long axis ratio, and the angle of rotation of the long axis relative to the horizontal direction. These capabilities are particularly important in the field of interferometric imaging and for the control of optical surfaces, especially in precision-machined optical whispering gallery mode resonators.
The Ring Analyzer is implemented in Python and requires Python version 2.6 or higher. To execute the program, users must provide an initial guess for several parameters: the filename of a PNG grayscale image, the initial ratio of the short to long axis (epsilon), the centroid position (x_0, y_0), and the angle of rotation. If the centroid position is set to -1 for both x_0 and y_0, the program defaults to the center of the image. The program also includes several assumptions and parameters that can be modified, such as threshold values, step sizes for searching parameters, and precision goals.
Upon execution, the program converts the input image into a two-dimensional array of pixel values, which are then analyzed to optimize the signal-to-noise ratio (SNR) of the data. The analysis involves iterative steps to refine the estimated parameters until they reach specified precision levels. The final results, including the optimized parameters, are printed to the screen, and a processed image file is saved for visual assessment.
The document also includes an example of the program's application, demonstrating how initial guesses can lead to refined estimates of the parameters. The analysis aims to produce a one-dimensional representation of the data that retains the essential features of the original image, allowing for effective visualization of the fringes.
Overall, the Ring Image Analyzer serves as a valuable tool for researchers and engineers working in fields that require precise optical measurements and analysis, contributing to advancements in aerospace technology and related applications.
