mirror of
https://github.com/wassname/scikit-image.git
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Vincent Albufera
56 lines
1.6 KiB
Python
56 lines
1.6 KiB
Python
"""
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===============================================================================
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Peak local maximum
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===============================================================================
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The peak local maximum return coordinates of peaks in a image. The maximum
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filter is used for finding the maximum peaks in the image. It dilates the
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original image and is used within peak local max function to find the
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coordinates of maximum peaks, comparing the dilated image with the original.
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Then, the peak local max function returns the coordinates of points where
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image = dilated image.
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"""
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from scipy import ndimage
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import matplotlib.pyplot as plt
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import numpy as np
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from skimage.feature import peak_local_max
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from skimage import data, img_as_float
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im = img_as_float(data.coins())
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image = im.copy()
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# The image_max is the dilation of im with a 20*20 structuring element
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# It is used within peak_local_max function
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image_max = ndimage.maximum_filter(image, size=20, mode='constant')
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# Comparison between image_max and im to find the coordinates of maximum peaks
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coordinates = peak_local_max(im, min_distance = 20)
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# display results
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plt.figure(figsize=(8, 3))
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plt.subplot(131)
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plt.imshow(im, cmap=plt.cm.gray)
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plt.axis('off')
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plt.title('Original')
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plt.subplot(132)
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plt.imshow(image_max, cmap=plt.cm.gray)
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plt.axis('off')
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plt.title('Maximum filter')
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plt.subplot(133)
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plt.imshow(im, cmap=plt.cm.gray)
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a, b = im.shape
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plt.plot([p[1] for p in coordinates],[p[0] for p in coordinates],'r.')
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plt.xlim(0,b)
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plt.ylim(a,0)
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plt.axis('off')
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plt.title('Peak local max')
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plt.subplots_adjust(wspace=0.02, hspace=0.02, top=0.9,
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bottom=0.02, left=0.02, right=0.98)
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plt.show()
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