将椭圆拟合到图像数据集

Question

我正在使用相机信号。摄像机的典型信号用以下模拟：

import cairo
import numpy
import matplotlib.pyplot as plt


data = numpy.zeros((352, 352), dtype = numpy.uint8)
surface = cairo.ImageSurface.create_for_data(
                        data, cairo.FORMAT_A8, 352, 352)

cr = cairo.Context(surface)
cr.scale(0.85, 1.15)
cr.arc(200, 150, 100, 0, 2. * numpy.pi)
cr.set_line_width(15)
cr.stroke()

plt.imshow(data, cmap = "gray", interpolation = "None")
plt.show()

从此图片数据集中，我需要获取以下参数：x-center，y-center，radius，thickness，ellipticity，{{1}白色椭圆环。

获得这些参数的快速准确方法是什么？

我多年来获得的代码片段是以下2D高斯拟合：

angle of the ellipse

但是，我无法将import scipy.odr def gauss_2D(p, r): # p = [amplitude, x-cen, y-cen, x-waist, y-waist, angle_in_rad, z-offset] x = r[0,] y = r[1,] dx, dy = (x - p[1]), (y - p[2]) xp = dx * numpy.cos(p[5]) + dy * numpy.sin(p[5]) yp = dy * numpy.cos(p[5]) - dx * numpy.sin(p[5]) data = (p[0] * numpy.exp(-2 * (xp / p[3])**2 - 2 * (yp / p[4])**2)) return data + p[6] def fit_gauss(p_guess, data_set): rr = numpy.indices(data_set.shape[:2]) N = rr.shape[1] * rr.shape[2] fix = [1, 1, 1, 1, 1, 1, 1] model = scipy.odr.Model(gauss_2D) data = scipy.odr.Data(rr.reshape((2, N)), data_set.reshape((1, N))) odr = scipy.odr.ODR(data, model, p_guess, ifixb = fix) odr.set_job(fit_type = 2) output = odr.run() coeff = output.beta coeff_sd = output.sd_beta return rr, coeff, coeff_sd 重写为适用于具有特定线条粗细的椭圆的函数。

感谢所有帮助！