Question

当我使用Hough变换时，我遇到了问题。我想检测虹膜图像中唯一的瞳孔。代码如下：



import cv2
from cv2 import cv
import numpy as np
import os

directory = os.listdir("/home/joker26/Scrivania/casia/test")
numero_file = len(directory)
for file in directory:
    print file
file_iride = raw_input("File(riportare anche estensione): ")
path = "/home/joker26/Scrivania/casia/test/%s" %(file_iride)
image_iride = cv2.imread(path)
output = image_iride.copy()
image_test = cv2.imread(path, cv2.CV_LOAD_IMAGE_GRAYSCALE)

image_test = cv2.Canny(image_test,5,70,apertureSize=3)
image_test = cv2.GaussianBlur(image_test, (7,7), 1)

cerchi = cv2.HoughCircles(image_test, cv2.cv.CV_HOUGH_GRADIENT,50, 100, 50,300)
if cerchi is not None:
    cerchi = np.round(cerchi[0,:]).astype("int")
    for (x,y,raggio) in cerchi:
        cv2.circle(output, (x,y),raggio,(255,0,0),4)
    cv2.imshow("Image test", np.hstack([image_iride,output]))
    cv2.waitKey()

import cv2 from cv2 import cv import numpy as np import os directory = os.listdir("/home/joker26/Scrivania/casia/test") numero_file = len(directory) for file in directory: print file file_iride = raw_input("File(riportare anche estensione): ") path = "/home/joker26/Scrivania/casia/test/%s" %(file_iride) image_iride = cv2.imread(path) output = image_iride.copy() image_test = cv2.imread(path, cv2.CV_LOAD_IMAGE_GRAYSCALE) image_test = cv2.Canny(image_test,5,70,apertureSize=3) image_test = cv2.GaussianBlur(image_test, (7,7), 1) cerchi = cv2.HoughCircles(image_test, cv2.cv.CV_HOUGH_GRADIENT,50, 100, 50,300) if cerchi is not None: cerchi = np.round(cerchi[0,:]).astype("int") for (x,y,raggio) in cerchi: cv2.circle(output, (x,y),raggio,(255,0,0),4) cv2.imshow("Image test", np.hstack([image_iride,output])) cv2.waitKey() 结果是： http://i.stack.imgur.com/LJOE9.png

Answer 1

检测瞳孔而不是虹膜有什么意义？它们都是眼睛的一部分。但是，您的错误在于测试数据。

您正在使用的测试数据，我认为是数千张人眼的照片。现在，您的计算机将学会识别这些照片中的内容，如果您的训练数据是全眼睛，它将显示全眼睛。该缺陷不在您的代码中，而是在您的代码正在访问的数据中。

Answer 2

您可以使用：

cerchi = cv2.HoughCircles(image_test, cv2.HOUGH_GRADIENT, 1.3, 800)

在虹膜识别python中检测瞳孔

2 个答案: