ICP 1.3

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

Version 1.3 is a major rewrite of the ICP module. While the previous versions of this module were useful primarily for binary images, the new version should also work well for grayscale and color images. The new module also contains improvements to the implementation code for the core ICP algorithm. It should be more forgiving should there exist no correspondents in one image for some of the pixels chosen for ICP calculations in the other image. Finally, this version gives you two options for applying ICP to grayscale and color images: You can carry out either edge-based ICP or corner-pixels based ICP.

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.