gen_projective_mosaic — Combine multiple images into a mosaic image.
gen_projective_mosaic combines the input images contained in the object Images into a mosaic image MosaicImage. The relative positions of the images are defined by 3x3 projective transformation matrices. The array HomMatrices2D contains a sequence of these linearized matrices. The values in MappingSource and MappingDest are the indices of the images that the corresponding matrix applies to. MappingSource=4 and MappingDest=7 means that the matrix describes the transformation of the image number 4 into the projective plane of image 7. The transformation matrices between the respective image pairs given by MappingSource and MappingDest are typically determined with proj_match_points_ransac.
As usual for operators that access image objects (e.g., select_obj), the images are numbered starting from 1, i.e., MappingSource, MappingDest, StartImage, and StackingOrder) must contain values between 1 and the number of images passed in Images.
The parameter StartImage states which image defines the image plane of the final image, that is, which input image remains unchanged in the output image. This is usually an image that is located near the center of the image mosaic.
The origin of MosaicImage and its size are automatically chosen so that all of the input images are completely visible.
The order in which the images are added to the mosaic is given by the array StackingOrder. The first index in this array will end up at the bottom of the image stack while the last one will be on top. If 'default' is given instead of an array of integers, the canonical order (images in the order used in Images) will be used.
The parameter TransformDomain can be used to determine whether the domains of Images are also transformed. Since the transformation of the domains costs runtime, this parameter should be used to specify whether this is desired or not. If TransformDomain is set to 'false' the domain of the input images is ignored and the complete images are transformed.
On output, the parameter MosaicMatrices2D contains a set of 3x3 projective transformation matrices that describe for each image in Images the mapping of the image to its position in the mosaic.
Index of the central input image.
Indices of the source images of the transformations.
Indices of the target images of the transformations.
Array of 3x3 projective transformation matrices.
Stacking order of the images in the mosaic.
Default value: 'default'
Suggested values: 'default'
Should the domains of the input images also be transformed?
Default value: 'false'
List of values: 'false', 'true'
Array of 3x3 projective transformation matrices that determine the position of the images in the mosaic.
gen_empty_obj (Images) for J := 1 to 6 by 1 read_image (Image, 'mosaic/pcb_'+J$'02') concat_obj (Images, Image, Images) endfor From := [1,2,3,4,5] To := [2,3,4,5,6] Num := |From| ProjMatrices :=  for J := 0 to Num-1 by 1 F := From[J] T := To[J] select_obj (Images, ImageF, F) select_obj (Images, ImageT, T) points_foerstner (ImageF, 1, 2, 3, 200, 0.3, 'gauss', 'false', \ RowJunctionsF, ColJunctionsF, CoRRJunctionsF, \ CoRCJunctionsF, CoCCJunctionsF, RowAreaF, \ ColAreaF, CoRRAreaF, CoRCAreaF, CoCCAreaF) points_foerstner (ImageT, 1, 2, 3, 200, 0.3, 'gauss', 'false', \ RowJunctionsT, ColJunctionsT, CoRRJunctionsT, \ CoRCJunctionsT, CoCCJunctionsT, RowAreaT, \ ColAreaT, CoRRAreaT, CoRCAreaT, CoCCAreaT) proj_match_points_ransac (ImageF, ImageT, RowJunctionsF, \ ColJunctionsF, RowJunctionsT, \ ColJunctionsT, 'ncc', 21, 0, 0, 480, 640, \ 0, 0.5, 'gold_standard', 1, 4364537, \ ProjMatrix, Points1, Points2) ProjMatrices := [ProjMatrices,ProjMatrix] endfor gen_projective_mosaic (Images, MosaicImage, 2, From, To, ProjMatrices, \ 'default', 'false', MosaicMatrices2D)
proj_match_points_ransac, proj_match_points_ransac_guided, vector_to_proj_hom_mat2d, hom_vector_to_proj_hom_mat2d
projective_trans_image, projective_trans_image_size, projective_trans_region, projective_trans_contour_xld, projective_trans_point_2d, projective_trans_pixel
Richard Hartley, Andrew Zisserman: “Multiple View Geometry in
Computer Vision”; Cambridge University Press, Cambridge; 2000.
Olivier Faugeras, Quang-Tuan Luong: “The Geometry of Multiple Images: The Laws That Govern the Formation of Multiple Images of a Scene and Some of Their Applications”; MIT Press, Cambridge, MA; 2001.