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A Python module for registering a photo with a database image of the same scene

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Consult the module API page at

https://engineering.purdue.edu/kak/distICP/ICP-2.1.1.html

for all information related to this module, including information related to the latest changes to the code. The page at the URL shown above lists all of the module functionality you can invoke in your own code. With regard to the new functionality added in Version 2.1.0, that page also describes how you can use the ICP algorithm in a scan mode when working with large images that are synthesized by collecting data from sensors in motions (as is the case with earth-observing satellites that use pushbroom cameras and, in some cases, with the images recorded by UAVs).

Version 2.1.1 fixes a bug that made itself evident when using ICP in the scanning mode with a non-square array of subimages.

Version 2.1.0 incorporates a new ICPImageScanner class that allows the ICP algorithm to be invoked in a scanning mode for subimage-based ICP registration of large model and data images. This version also includes a bugfix needed to make the module work with the more recent versions of the Pillow library for PIL. This version also includes a constructor option for specifying your own font file needed for displaying the results.

Version 2.0 is a Python 3.x compliant version of the ICP module. This version should work with both Python 3.x and Python 2.7.

An application scenario would be the registration of an image recorded by a UAV-mounted camera flying over a terrain with an image extracted from a GIS (Geographical Information System) database.

Typical usage syntax for a color or grayscale image when using edge-based ICP:

import ICP
icp = ICP.ICP(
           binary_or_color = "color",
           corners_or_edges = "edges",
           auto_select_model_and_data = 1,
           calculation_image_size = 200,
           max_num_of_pixels_used_for_icp = 300,
           pixel_correspondence_dist_threshold = 20,
           iterations = 24,
           model_image =  "SydneyOpera.jpg",
           data_image = "SydneyOpera2.jpg",
         )
icp.extract_pixels_from_color_image("model")
icp.extract_pixels_from_color_image("data")
icp.icp()
icp.display_images_used_for_edge_based_icp()
icp.display_results_as_movie()
icp.cleanup_directory()

Here is example syntax for using corner-pixels based ICP:

import ICP
icp = ICP.ICP(
           binary_or_color = "color",
           corners_or_edges = "corners",
           calculation_image_size = 200,
           image_polarity = -1,
           smoothing_low_medium_or_high = "medium",
           corner_detection_threshold = 0.2,
           pixel_correspondence_dist_threshold = 40,
           auto_select_model_and_data = 1,
           max_num_of_pixels_used_for_icp = 100,
           iterations = 16,
           model_image =  "textured.jpg",
           data_image = "textured2.jpg",
        )
icp.extract_pixels_from_color_image("model")
icp.extract_pixels_from_color_image("data")
icp.icp()
icp.display_images_used_for_corner_based_icp()
icp.display_results_as_movie()
icp.cleanup_directory()

Yet another mode for using the module is for registering binary images. The Examples directory contains six canned scripts that illustrate the different ways of using this module.

For the new functionality that was added in Version 2.1.0, see the ExamplesICPImageScanner directory for how to invoke that functionality for first chopping large images into subimages and then applying ICP separately to each corresponding pair of subimages.

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