SETUP_GRID: Create a grid for points (shapes) to be embedded
in.
Code written by Katherine Smith, 2003
GENERAL
[grid, steps] = setup_grid(image_width, unwarped_image,
unwarped_points, placement_method, n_points)
INPUT/S
-image_width:
The width of the input image.
-unwarped_image:
The input image.
-unwarped_points:
The control points of this image.
-placement_method:
One of: 'overlap grid', 'grid', 'random',
'random_and_scale', 'edge', 'edge_and_scale'.
-n_points:
Number of points in grid?
OUTPUT/S
-grid:
The grid in 1-D
-steps:
The steps on the grid in 1-D
PENDING WORK
-
KNOWN BUG/S
-
COMMENT/S
-steps must be specified for single-point warps but not for
multi-point warps
RELATED FUNCTION/S
ABOUT
-Created: November 23rd, 2003
-Last update: Novermber 25th, 2003
-Revision: 0.0.2
-Author: R. S. Schestowitz, University of Manchester
==============================================================0001 function [grid, steps] = setup_grid(image_width, unwarped_image, unwarped_points, placement_method, n_points) 0002 % SETUP_GRID: Create a grid for points (shapes) to be embedded 0003 % in. 0004 % 0005 % Code written by Katherine Smith, 2003 0006 % 0007 % GENERAL 0008 % 0009 % [grid, steps] = setup_grid(image_width, unwarped_image, 0010 % unwarped_points, placement_method, n_points) 0011 % 0012 % INPUT/S 0013 % 0014 % -image_width: 0015 % The width of the input image. 0016 % 0017 % -unwarped_image: 0018 % The input image. 0019 % 0020 % -unwarped_points: 0021 % The control points of this image. 0022 % 0023 % -placement_method: 0024 % One of: 'overlap grid', 'grid', 'random', 0025 % 'random_and_scale', 'edge', 'edge_and_scale'. 0026 % 0027 % -n_points: 0028 % Number of points in grid? 0029 % 0030 % OUTPUT/S 0031 % 0032 % -grid: 0033 % The grid in 1-D 0034 % 0035 % -steps: 0036 % The steps on the grid in 1-D 0037 % 0038 % PENDING WORK 0039 % 0040 % - 0041 % 0042 % KNOWN BUG/S 0043 % 0044 % - 0045 % 0046 % COMMENT/S 0047 % 0048 % -steps must be specified for single-point warps but not for 0049 % multi-point warps 0050 % 0051 % RELATED FUNCTION/S 0052 % 0053 % 0054 % 0055 % ABOUT 0056 % 0057 % -Created: November 23rd, 2003 0058 % -Last update: Novermber 25th, 2003 0059 % -Revision: 0.0.2 0060 % -Author: R. S. Schestowitz, University of Manchester 0061 % ============================================================== 0062 0063 steps = []; 0064 0065 switch placement_method, 0066 0067 case 'overlap_grid' 0068 ctr = 1; 0069 for i=1:5 0070 step = 2 / (i + 1); % 2/2=1, 2/3, 2/4=1/2, 2/5... 0071 for j=1:i % will execute 1,2,3... times 0072 grid(ctr)= -1 + j * step; % 0 + stepsize*number of steps 0073 steps(ctr) = step; % CTR STANDS FOR COUNTER, NOT CENTRE - save corresponding step size 0074 ctr = ctr + 1; % increment step index 0075 end 0076 end 0077 0078 case 'grid' 0079 grid = -0.9:0.2:0.9; % divide into 10 segments (10 lines or knot-points) 0080 0081 case 'alternating_grid' 0082 % random_number = rand; 0083 % if (rand < 0.3) 0084 % grid = -0.9:0.2:0.9; % divide into 10 segments 0085 % elseif (rand > 0.7) 0086 % grid = -0.9:0.3:0.9; % divide into 7 segments 0087 % else 0088 % grid = -0.8:0.4:0.8; % divide into 5 segments 0089 % end 0090 grid = -0.45:0.1:0.45; 0091 % ...still to be modified... 0092 0093 case 'random' 0094 for ctr = 1:n_points 0095 grid(ctr) = rand * 2 - 1; % choose one to begin with... do-while loop would fit better here 0096 while(min(abs(grid(1:ctr-1) - grid(ctr))) < 0.01) % find the minimum of the differences and ensure it is very small 0097 grid(ctr) = rand * 2 - 1; % generate the next random value for a line margin in the grid until it's a good choice 0098 end 0099 end 0100 0101 case 'random_and_scale' 0102 % width is only used here, but it is not really image width!! 0103 for ctr = 1:n_points 0104 steps(ctr) = image_width + 1; 0105 while (steps(ctr) > image_width / 2) % iterate until the value is good enough, i.e. small enough 0106 steps(ctr) = abs(randn(1)) * (image_width / 2) * 0.7; % some mysterious formulation 0107 end 0108 grid(ctr) = -1 + steps(ctr) + rand * (image_width - 2 * steps(ctr)); % set grid according to step above and apply some randomisation to step size too 0109 % grid(ctr) = steps(ctr) + 1 + rand*(image_width - 2*steps(ctr)); 0110 end 0111 0112 case 'edge' 0113 % Smith: put knotpoints on n_knots strongest edges 0114 % RSS: steps however is not set, hence no 'scale' 0115 n_knots = n_points; 0116 % Smith set this to 2 0117 edges = diff(unwarped_image); 0118 [dummy,indices] = sort(abs(edges)); 0119 indices = flipud(indices); 0120 which = indices(1:n_knots); 0121 grid = unwarped_points(which); 0122 0123 case 'edge_and_scale' 0124 % put knotpoints on n_knots strongest edges 0125 n_knots = n_points; 0126 % Smith set this to 2 for bump data 0127 edges = diff(unwarped_image); 0128 [dummy,indices] = sort(abs(edges)); 0129 % absolute value as we do not account for "mirroring" effects 0130 indices = flipud(indices); 0131 % sort them by magnitude 0132 which = indices(1:n_knots); 0133 % choose these which are the strongest n edges 0134 grid = unwarped_points(which); 0135 steps = min([1 - abs(grid), 1 + abs(grid)], [], 2); 0136 0137 otherwise 0138 error(['Placement method ',placement_method,' is unknown']); 0139 end