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Major Sync Errors Removed. Parallel Loops added. #5

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80658fa
15-03-2015
IndraTheZeus Mar 15, 2019
2a07747
Error Detection Lines added
IndraTheZeus Mar 17, 2019
a32e956
Major Sync Error Removal 17-03-2019
IndraTheZeus Mar 17, 2019
477689d
Removed Unnecessary Variables from workplace
IndraTheZeus Mar 17, 2019
0b0d04b
Update GetAllFeatures.m
IndraTheZeus Mar 17, 2019
f61dc9d
Update BinningGL.m
IndraTheZeus Mar 17, 2019
705cc5a
19-03-2019
IndraTheZeus Mar 19, 2019
c16779c
BoundingBox error removed
IndraTheZeus Mar 19, 2019
81fc3bb
Update GetBoundingBoxes.m
IndraTheZeus Mar 20, 2019
652b7ff
Extracted for 4
IndraTheZeus Mar 20, 2019
2d05969
Sensetivity to be removed
IndraTheZeus Mar 20, 2019
5b2581f
20-03-2019
IndraTheZeus Mar 20, 2019
18c9498
Debugging Alignment done
IndraTheZeus Mar 24, 2019
2b95dcc
25-03-2019
IndraTheZeus Mar 25, 2019
db37cc2
27-03-2019
IndraTheZeus Mar 27, 2019
eb4a9a8
ideal Values added
IndraTheZeus Mar 29, 2019
94bf745
masking Problem eliminated
IndraTheZeus Apr 2, 2019
a8a74de
Ideal Values added
IndraTheZeus Apr 3, 2019
b397e9c
accuracy calculation changed
IndraTheZeus Apr 4, 2019
d6beea5
Scaling factor added
IndraTheZeus Apr 5, 2019
8a80834
10 Images extracted
IndraTheZeus Apr 22, 2019
7ddca26
10 images extraction done
IndraTheZeus May 11, 2019
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222 changes: 222 additions & 0 deletions BackupGetBoundingBox.m
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Original file line number Diff line number Diff line change
@@ -0,0 +1,222 @@
%
%
%% BACKUP FOR GET BOUNDING BOX
%
%
% function [BoundingBoxes] = GetBoundingBoxes(CCs,CCstats,Features,NeedToStabilize,hasParametersSupplied,Parameters)
%
% BoundingBoxes = zeros(1,4);
% Features = abs(Features);
% % NOTE: The Feature Values supplied need to be of already stable
% % componenets if hasParametersSupplied is false.
%
% %% Features
%
% % 1. Lower Range Pixel Deviatiion ([0,1])
% % 2. Higher Range Pixel Deviation ([0,1])
% % 3. Lower Range change of Euler Number/100([0,1))
% % 4. Higher Range change of Euler Number/100([0,1))
% % 5. Lower Range Density Deviation ([0,1])
% % 6. Higher Range Density Deviation ([0,1])
% % 7. No. of Pixels [0,1)
% % 8. Height [0,1)
% % 9. Width [0,1)
% % 10. Solidity [0,1]
% % 11. Euler/100 [0,1)
%
% % 12 Eccentricity [0,1]
% % 13. Extent [0,1]
% % 14. SVT [0,1]
% % 15. eHOG [0,1]
%
% %% PARAMETERS
%
% % 1. Max Lower Range No. of Pixels Deviation Allowed ( Value > 0 and Value < 1 )
% % 2. Max Higher Range No. of Pixels Deviation Allowed ( Value > 0 and Value < 1)
% % 3. Max Euler Number/100( Value > 1 and Value < Infinite )
% % 4. Max Difference in Euler Number for Lower Range/100( 0 <= Value < 1 )
% % 5. Max Difference in Euler Number for Higher Range/100( 0 <= Value < 1 )
% % 6. Max Solidity ( Value > 0 and Value < 1)
% % 7. Min Solidity ( Value > 0 and Value < 1)
% % 8. Max Lower Range Density Deviation Allowed ( 0 < Value < 1 )
% % 9. Max Higher Range Density Deviation Allowed ( 0 < Value < 1 )
% % 10. Max No. of Pixels Ratio
% % 11. Min No. of Pixels Ratio
% % 12. Max Height Ratio
% % 13. Min Height Ratio
% % 14. Max Width Ratio
% % 15. Min Width Ratio
%
%
% % 16. Baseline Deviation by average height for aligned ( 0 < Value < 1 )
% % 17. Spacing Deviation by average height for aligned (0 < value < 1 )
% % 18. Height Difference by average height for aligned ( 0 < Value < 1 )
% % 19. Maximum negative starting point by average height for aligned (0 < Value < 1)
%
%
% % 20. Max Average Solidity for aligned ( 0 < Value < 1)
% % 21. Min Average Solidity for aligned ( 0 < Value < Max Solidity)
% % 22. Max Average Euler Number for aligned ( 0 < Value < 1)
% % 23. Min Average Euler Number for aligned ( 0 < Value < Max Euler)
% % 24. Max Average Eccentricity for Aligned ( 0 < Value < 1)
% % 25. Min Average Eccentricity for Aligned ( 0 < Value < Max Eccentricity)
% % 26. Max Average Extent for aligned ( 0 < Value < 1)
% % 27. Min Average Extent for aligned ( 0 < Value < Max Extent)
% % 28. Max Average SVT for aligned ( 0 < Value < 1)
% % 29. Max Average eHOG for aligned ( 0 < Value < 1)
%
% % 30. Max Solidity [0,1]
% % 31. Min Solidity [0,Max Solidity]
% % 32. Max Euler Number [0,1)
% % 33. Min Euler Number [0,Max Euler)
% % 34. Max Eccentricity [0,1]
% % 35. Min Eccentricity [0,Max Eccentricity]
% % 36. Max Extent [0,1]
% % 37. Min Extent [0, Max Extent)
% % 38. Max SVT [0,1]
% % 39. Max eHOG [0,1]
%
% % data = [0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.25 0.5 0.25 0.5
% % 0.25 0.25 0.25 0.25 0.25 0.8 0.1 0.06 0 0.98 0 0.9 0 0.25 0.3
% % 0.65 0.1 0.06 0 0.99 0 0.9 0.2 0.25 0.3]
% %% Parameter Initialization
%
% if hasParametersSupplied
% GroupingParams = Parameters(1,16:19); % PARAMETER ARRAY DEPENDENT
% AlignedGroupParams_MAX = [Parameters(1,20:2:26) Parameters(1,28:29)];
% AlignedGroupParams_MIN = [Parameters(1,21:2:27) 0 0];
% AlignedGroupParams_MAX = AlignedGroupParams_MAX + AlignedGroupParams_MIN;
% NonAlignedGroupParams_MAX = [Parameters(1,30:2:36) Parameters(1,38:39)];
% NonAlignedGroupParams_MIN = [Parameters(1,31:2:37) 0 0];
% NonAlignedGroupParams_MAX = NonAlignedGroupParams_MAX + NonAlignedGroupParams_MIN;
% else % DEFAULT VALUES
% GroupingParams = [ 0.25 0.25 0.25 0.25 ];
% AlignedGroupParams_MAX = [ 0.8 0.06 0.98 0.9 0.25 0.3];
% AlignedGroupParams_MIN = [0.1 0 0 0.2 0 0];
% NonAlignedGroupParams_MAX = [0.65 0.06 0.99 0.9 0.25 0.3];
% NonAlignedGroupParams_MIN = [ 0.1 0 0 0.2 0 0];
% end
%
%
% %% CODE
% start = 1;
% numBBs = 0;
% component_class = zeros(size(Features,1),1); % Vector Denoting Class
% % 0 - Undecided
% % 1 - Non Text
% % 2 - Text
% % 3 - Stable Component
%
% for i = 1:size(CCs,2)
% if CCs(1,i) == 0
% continue;
% end
% ends = CCs(1,i);
%
% for comp = start:ends
% if component_class(comp,1) == 1 || component_class(comp,1) == 2 %If already classified,skip over
% continue
% end
%
% if NeedToStabilize && component_class(comp,1) == 0
% if hasParametersSupplied
% [isStable] = PredictStabilityFromParameters(Features(comp,1:11),Parameters(1,1:15));
% else
% error('Need to supply Parameters if Unstable components supplied');
% end
%
% if ~isStable
% component_class(comp,1) = 1;
% continue
% else
% component_class(comp,1) = 3;
% end
% end % Stabilization done
%
%
% stats = CCstats(comp,:);
%
% avg_height = stats(1,4);
% avg_baseline = stats(1,2) + stats(1,4);
% max_y = stats(1,1) + stats(1,3);
% max_x = stats(1,2) + stats(1,4);
% aligned_comps = zeros(1,20); % An Array of aligned comp labels, BUFFER OF UPTO 20 ALIGNED COMPONENTS
% aligned_comps(1,:) = comp;
% aligns = 1;
% sum_features = Features(comp,10:15);
%
% BB = stats(:,:);
%
% for scan_comp = (comp+1):ends
%
% if component_class(scan_comp,1) ~= 0 && component_class(scan_comp,1) ~= 3
% continue;
% end
%
% if NeedToStabilize && component_class(scan_comp,1) == 0
% if hasParametersSupplied
% [isStable] = PredictStabilityFromParameters(Features(scan_comp,1:11),Parameters(1,1:15));
% else
% error('Need to supply Parameters if Unstable components supplied');
% end
%
% if ~isStable
% component_class(scan_comp,1) = 1;
% continue
% else
% component_class(scan_comp,1) = 3;
% end
% end %Stabilization done
%
%
% scan_stats = CCstats(scan_comp,:);
% spacing_dev = abs(scan_stats(1,1) - max_y)/avg_height;
% if spacing_dev > 1.25*GroupingParams(1,2) % CRITICAL ASSUME: Once components reach a certain distance horizontally,it keeps on increasing
% break;
% end
% baseline_dev = abs(scan_stats(1,2) + scan_stats(1,4) - avg_baseline)/avg_height;
% height_dev = abs(scan_stats(1,4) - avg_height)/avg_height;
% startPoint_diff = (max_y - scan_stats(1,1))/avg_height;
%
% C_Arr = [baseline_dev spacing_dev height_dev startPoint_diff];
% isAligned = C_Arr <= GroupingParams;
%
% if isAligned == 1
%
% avg_height = (avg_height*aligns + scan_stats(1,4))/(aligns+1);
% avg_baseline = (avg_baseline*aligns + (scan_stats(1,2) + scan_stats(1,4)))/(aligns+1);
% max_y = max(max_y,scan_stats(1,1)+scan_stats(1,3));
% max_x = max(max_x,scan_stats(1,2)+scan_stats(1,4));
% aligns = aligns + 1;
% aligned_comps(1,aligns) = scan_comp;
% sum_features = sum_features + Features(scan_comp,10:15);
%
% BB(1,1) = min(BB(1,1),scan_stats(1,1)); %%Increasing the Bounding Box
% BB(1,3) = max_y - BB(1,1);
% BB(1,2) = min(BB(1,2),scan_stats(1,2));
% BB(1,4) = max_x - BB(1,2);
% end
%
% end
%
% C_Arr = sum_features./aligns;
%
% if aligns > 1
% isTextGroup = (C_Arr <= AlignedGroupParams_MAX) & (C_Arr >= AlignedGroupParams_MIN);
% else
% isTextGroup = (C_Arr <= NonAlignedGroupParams_MAX ) & ( C_Arr >= NonAlignedGroupParams_MIN );
% end
%
% if isTextGroup == 1
% numBBs = numBBs + 1;
% BoundingBoxes(numBBs,:) = BB;
% component_class(aligned_comps,1) = 2;
% else
% component_class(aligned_comps,1) = 1;
% end
%
% end
% start = ends + 1;
% end
%
% end
Binary file added BinImages2.mat
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38 changes: 26 additions & 12 deletions Binning.m
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Original file line number Diff line number Diff line change
@@ -1,12 +1,11 @@
function [BinImages,NUM_BIN_IMAGES,MAX_DISTANCE] = Binning( image,BinSizes)

function [NUM_BIN_IMAGES,MAX_DISTANCE] = Binning( image,BinSizes)
global BinImages
%% This function Bins the images based on BinSizes and returns a set of Binary Images(:BinSizes) ,the number of such Images(:BUM_BIN_IMAGES)
% And the maximum value of a pixel(for grey scale it's 255)
%CODE

image = histeq(image);


MAX_DISTANCE = 255;

NUM_BIN_IMAGES = calculateNumBins_2Level(BinSizes,MAX_DISTANCE);
Expand All @@ -17,37 +16,52 @@

BinImages = false(row,col,NUM_BIN_IMAGES);


BinMatrix = GetBinAllocations(BinSizes,MAX_DISTANCE,NUM_BIN_IMAGES);

q_offset = 0;
DistanceMatrix = zeros(row,col);

for r = 1:row
for c = 1:col

if size(image,3) == 1
DistanceMatrix(r,c) = image(r,c); %%ASSUMED GRAY SCALE IMAGE,OTHERWISE VALUE ARE RGB Euclidean distance
DistanceMatrix(r,c) = double(image(r,c)); %%ASSUMED GRAY SCALE IMAGE,OTHERWISE VALUE ARE RGB Euclidean distance
else
DistanceMatrix(r,c) = image(r,c);
DistanceMatrix(r,c) = double(image(r,c));
end

end
end

for i = 1:numel(BinSizes)
main_offset = ceil(MAX_DISTANCE/BinSizes(i));
k = ceil((BinSizes(i)/2)) -1;
for i = 1:size(BinSizes,2)

main_offset = ceil(MAX_DISTANCE/BinSizes(1,i));
k = ceil((BinSizes(1,i)/2)) -1;
% fprintf("\nMapping Image to Bin Size: %d",BinSizes(i));
for r = 1:row
for c = 1:col

value = DistanceMatrix(r,c);

x = q_offset+floor(value/BinSizes(i))+1;
x = q_offset+floor(value/BinSizes(1,i))+1;
% if x > size(BinImages,3)
% error('Wrong calculation of NumberBinImages');
% end
BinImages(r,c,x) = 1;
% if BinMatrix(x,3) > value || BinMatrix(x,4) < value
% warning("ERROR:: ");
% fprintf("\nERROR; VALUES ARE NOT MAPPING TO BIN_MATRIX for pixel value= %d , Mapped to Main Bin = %d\n",value,x);
% end

if value>k && value<(((main_offset-1)*BinSizes(i))+k) %%CHANGES IN MAX DISTANCE MADE
y = q_offset+main_offset+ceil((value-k)/BinSizes(i));
if value>k && value<(((main_offset-1)*BinSizes(1,i))+k) %%CHANGES IN MAX DISTANCE MADE
y = q_offset+main_offset+ceil((value-k)/BinSizes(1,i));
% if y > size(BinImages,3)
% error('Wrong calculation of NumberBinImages');
% end
BinImages(r,c,y) = 1;
% if BinMatrix(y,3) > value || BinMatrix(y,4) < value
% fprintf("\nERROR; VALUES ARE NOT MAPPING TO BIN_MATRIX for pixel value= %d , Mapped to Offset Bin = %d, k = %d Main_offset*BinSizes = %d\n",value,y,k,(((main_offset-1)*BinSizes(i))+k+1));
% end
end

end
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