Hello, Thank you for your question

If you have X-ray CT data of fiber-reinforced composites and want to determine the orientation of individual fibers, you have a few good options:

In short, Avizo is great for advanced features and ease of use, while ImageJ and Python/MATLAB offer more flexibility if you're comfortable with custom coding.

With best regards

You can use Python scripting.

• Set up Python Environment,
• Install the required libraries. OpenCV, NumPy, and Matplotlib.
• Write and Run your Script fib_orient.py:

Steps

• 1.Image Loading and Preprocessing:
• 2.Fiber Segmentation:
• 3.Feature Extraction:
• 4.Azimuthal Angle Calculation:
• 5.Visualization and Analysis

Overview of a script that reads X-ray CT data (e.g., TIFF, DICOM).

import cv2

import numpy as np

import matplotlib.pyplot as plt

# Load the image

img = cv2.imread('ct_image.tif', cv2.IMREAD_GRAYSCALE)

# 1.Image Preprocessing: (e.g., thresholding)

_, thresh = cv2.threshold(img, 128, 255, cv2.THRESH_BINARY)

# Find contours 2.Fiber Segmentation:

#3.Feature Extraction:

contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

# Create a histogram of fiber orientations

plt.hist(fiber_orientations, bins=20, edgecolor='black')

plt.xlabel('Fiber Orientation (degrees)')

plt.ylabel('Count')

# Visualize the fibers with orientation arrows

fig, ax = plt.subplots()

ax.imshow(img, cmap='gray')

plt.title('Fiber Orientation Visualization')

plt.show()

or # Histogram of azimuthal angles

plt.hist(azimuth_angles, bins=20, edgecolor='black')

plt.polar(azimuth_angles, [1] * len(azimuth_angles), marker='o')

plt.show()