关于Harris算法与SIFT算法特征匹配处理对比

*一.Harris算法
Harris角点检测算法是一个极为简单的角点检测算法。该算法的主要思想是，如果像素周围显示存在多于一个方向的边，我们认为该点为兴趣点。该点就称为角点。
以下是代码：

# -*- coding: utf-8 -*-
from pylab import *
from PIL import Image
from PCV.localdescriptors import harris
from PCV.tools.imtools import imresize

"""
This is the Harris point matching example in Figure 2-2.
"""

#im1 = array(Image.open("../data/crans_1_small.jpg").convert("L"))
#im2= array(Image.open("../data/crans_2_small.jpg").convert("L"))

im1 = array(Image.open("1.jpg").convert("L"))
im2 = array(Image.open("2.jpg").convert("L"))

im1 = imresize(im1, (im1.shape[1]//2, im1.shape[0]//2))
im2 = imresize(im2, (im2.shape[1]//2, im2.shape[0]//2))

wid = 5
harrisim = harris.compute_harris_response(im1, 5)
filtered_coords1 = harris.get_harris_points(harrisim, wid+1)
d1 = harris.get_descriptors(im1, filtered_coords1, wid)

harrisim = harris.compute_harris_response(im2, 5)
filtered_coords2 = harris.get_harris_points(harrisim, wid+1)
d2 = harris.get_descriptors(im2, filtered_coords2, wid)

print('starting matching')
matches = harris.match_twosided(d1,d2)

figure()
gray() 
harris.plot_matches(im1, im2, filtered_coords1, filtered_coords2, matches)
show()

运行结果如下：

二.SIFT(尺度不变特征变换）
SIFT特征对于尺度，旋转和亮度都具有不变形，因此，它可以用于三维视角和噪声的可靠匹配。

以下是SIFT代码的运用：

from PIL import Image
from pylab import *
import sys
from PCV.localdescriptors import sift


if len(sys.argv) >= 3:
  im1f, im2f = sys.argv[1], sys.argv[2]
else:
#  im1f = '../data/sf_view1.jpg'
#  im2f = '../data/sf_view2.jpg'
  im1f = '3.jpg'
  im2f = '4.jpg'
#  im1f = '../data/climbing_1_small.jpg'
#  im2f = '../data/climbing_2_small.jpg'
im1 = array(Image.open(im1f))
im2 = array(Image.open(im2f))

sift.process_image(im1f, 'out_sift_1.txt')
l1, d1 = sift.read_features_from_file('out_sift_1.txt')
figure()
gray()
subplot(121)
sift.plot_features(im1, l1, circle=False)

sift.process_image(im2f, 'out_sift_2.txt')
l2, d2 = sift.read_features_from_file('out_sift_2.txt')
subplot(122)
sift.plot_features(im2, l2, circle=False)

#matches = sift.match(d1, d2)
matches = sift.match_twosided(d1, d2)
print (('{} matches').format(len(matches.nonzero()[0])))

figure()
gray()
sift.plot_matches(im1, im2, l1, l2, matches, show_below=True)
show()

下面是运行结果：