Peak Detection Algorithm for 2D Array Paw Pressure Measurements
In order to segment the pressure measurements of dog paws into distinct anatomical regions, a local maximum filter can be employed.
Local Maximum Filter Implementation
<code class="python">import numpy as np from scipy.ndimage.filters import maximum_filter from scipy.ndimage.morphology import generate_binary_structure, binary_erosion from scipy.ndimage.measurements import label def detect_peaks(image): """ Utilizes a local maximum filter to identify and return a mask of peak locations. """ # Defines an 8-connected neighborhood neighborhood = generate_binary_structure(2,2) # Detects local maxima local_max = maximum_filter(image, footprint=neighborhood)==image # Creates a mask of the background background = (image==0) # Erodes the background to isolate peaks eroded_background = binary_erosion(background, structure=neighborhood, border_value=1) # Generates the final mask by removing background from the local_max mask detected_peaks = local_max ^ eroded_background return detected_peaks</code>
Usage and Post-Processing
Note:
Considerations for Implementation Enhancements:
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