Module: ImageMatch

Defined in:
lib/image_match.rb,
lib/image_match/version.rb

Constant Summary collapse

VERSION = 
"0.0.2"

Instance Method Summary collapse

Instance Method Details

#compare_surf_descriptors(d1, d2, best, length) ⇒ Object

Private functions

Raises:

  • (ArgumentError) 


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# File 'lib/image_match.rb', line 11

def compare_surf_descriptors(d1, d2, best, length)
  raise ArgumentError unless (length % 4) == 0
  total_cost = 0
  0.step(length - 1, 4) { |i|
    t0 = d1[i] - d2[i]
    t1 = d1[i + 1] - d2[i + 1]
    t2 = d1[i + 2] - d2[i + 2]
    t3 = d1[i + 3] - d2[i + 3]
    total_cost += t0 * t0 + t1 * t1 + t2 * t2 + t3 * t3
    break if total_cost > best
  }
  total_cost
end

#find_pairs(template_keypoints, template_descriptors, scene_keypoints, scene_descriptors) ⇒ Object 



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# File 'lib/image_match.rb', line 49

def find_pairs(template_keypoints, template_descriptors, scene_keypoints, scene_descriptors)
  ptpairs = []
  template_descriptors.size.times { |i|
    kp = template_keypoints[i]
    descriptor = template_descriptors[i]
    nearest_neighbor = naive_nearest_neighbor(descriptor, kp.laplacian, scene_keypoints, scene_descriptors)
    unless nearest_neighbor.nil?
      ptpairs << i
      ptpairs << nearest_neighbor
    end
  }
  ptpairs
end

#fuzzy_match_template(scene_filename, template_filename, is_output = false) ⇒ Boolean

Try to find 2nd input image in 1st input image. This function ignores color, size and shape details. (I mean this func checks whether almost same or clearly different)

Note that this function is useful I think, but sometimes it doesn’t output correct result which you want. It depends on input images. TODO : improve accuracy

Parameters:

  • scene_filename (String) —

    Scene image file path

  • template_filename (String) —

    template image file path which you want find in scene image

  • is_output (Boolean) (defaults to: false) —

    if you set true, you can get match result with image (default is false)

Returns:

  • (Boolean) —

    true if 1st input image seems to have 2nd input image false otherwise

Raises:

  • (ArgumentError) 


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# File 'lib/image_match.rb', line 187

def fuzzy_match_template(scene_filename, template_filename, is_output=false)
  raise ArgumentError, 'File does not exists.' unless File.exist?(scene_filename) and File.exist?(template_filename)
  raise ArgumentError, 'is_output must be true or false.' unless is_output == false or is_output == true
	
  scene, template = nil, nil
  begin  
    scene    = IplImage.load(scene_filename, CV_LOAD_IMAGE_GRAYSCALE)
	  template = IplImage.load(template_filename, CV_LOAD_IMAGE_GRAYSCALE)
  rescue
    raise RuntimeError, 'Couldn\'t read image files correctly'
    return false
  end

  return false unless scene.width >= template.width and scene.height >= template.height
	
	param = CvSURFParams.new(1500)
  template_keypoints, template_descriptors = template.extract_surf(param)
	scene_keypoints, scene_descriptors       = scene.extract_surf(param)
	
	src_corners = [CvPoint.new(0, 0), 
                 CvPoint.new(template.width, 0),
	               CvPoint.new(template.width, template.height),
                 CvPoint.new(0, template.height)]
	dst_corners = locate_planar_template(template_keypoints, 
                                     template_descriptors,
	                                   scene_keypoints,
                                     scene_descriptors,
                                     src_corners)


  if is_output
	  correspond = IplImage.new(scene.width, template.height + scene.height, CV_8U, 1);
	  correspond.set_roi(CvRect.new(0, 0, template.width, template.height))
	  template.copy(correspond)
	  correspond.set_roi(CvRect.new(0, template.height, scene.width, scene.height))
	  scene.copy(correspond)
	  correspond.reset_roi	
	  correspond = correspond.GRAY2BGR

    if dst_corners
	    4.times { |i|
	      r1 = dst_corners[i % 4]
	      r2 = dst_corners[(i + 1) % 4]
	      correspond.line!(CvPoint.new(r1.x, r1.y + template.height),
                         CvPoint.new(r2.x, r2.y + template.height),
	                       :color => CvColor::Red,
                         :thickness => 2, :line_type => :aa)
	    }
    end
	
    ptpairs = find_pairs(template_keypoints, template_descriptors, scene_keypoints, scene_descriptors)
	
	  0.step(ptpairs.size - 1, 2) { |i|
	    r1 = template_keypoints[ptpairs[i]]
	    r2 = scene_keypoints[ptpairs[i + 1]]
	    correspond.line!(r1.pt, CvPoint.new(r2.pt.x, r2.pt.y + template.height),
	                     :color => CvColor::Red, :line_type => :aa)
	  }
	
	  correspond.save_image(Time.now.to_i.to_s + "_match_result.png")
  end
  
  return (dst_corners ? true : false)
end

#locate_planar_template(template_keypoints, template_descriptors, scene_keypoints, scene_descriptors, src_corners) ⇒ Object 



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# File 'lib/image_match.rb', line 63

def locate_planar_template(template_keypoints, template_descriptors, scene_keypoints, scene_descriptors, src_corners)
  ptpairs = find_pairs(template_keypoints, template_descriptors, scene_keypoints, scene_descriptors)
  n = ptpairs.size / 2
  
  return nil if n < 4

  pt1 = []
  pt2 = []
  n.times { |i|
    pt1 << template_keypoints[ptpairs[i * 2]].pt
    pt2 << scene_keypoints[ptpairs[i * 2 + 1]].pt
  }

  _pt1 = CvMat.new(1, n, CV_32F, 2)
  _pt2 = CvMat.new(1, n, CV_32F, 2)
  _pt1.set_data(pt1)
  _pt2.set_data(pt2)
  h = CvMat.find_homography(_pt1, _pt2, :ransac, 5)

  dst_corners = []
  4.times { |i|
    x = src_corners[i].x
    y = src_corners[i].y
    z = 1.0 / (h[6][0] * x + h[7][0] * y + h[8][0])
    x = (h[0][0] * x + h[1][0] * y + h[2][0]) * z
    y = (h[3][0] * x + h[4][0] * y + h[5][0]) * z
    dst_corners << CvPoint.new(x.to_i, y.to_i)
  }

  dst_corners
end

#naive_nearest_neighbor(vec, laplacian, model_keypoints, model_descriptors) ⇒ Object 



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# File 'lib/image_match.rb', line 25

def naive_nearest_neighbor(vec, laplacian, model_keypoints, model_descriptors)
  length = model_descriptors[0].size
  neighbor = nil
  dist1 = 1e6
  dist2 = 1e6

  model_descriptors.size.times { |i|
    kp = model_keypoints[i]
    mvec = model_descriptors[i]
    next if laplacian != kp.laplacian
    
    d = compare_surf_descriptors(vec, mvec, dist2, length)
    if d < dist1
      dist2 = dist1
      dist1 = d
      neighbor = i
    elsif d < dist2
      dist2 = d
    end
  }

  return (dist1 < 0.6 * dist2) ? neighbor : nil
end

#perfect_match(image1_filename, image2_filename, limit_similarity = 0.9) ⇒ Boolean

Calculate matching score of 1st input image and 2nd input image required the sizes are same.

Parameters:

  • image1_filename (String) —

    Compare target image1 file path

  • image2_filename (String) —

    Compare target image2 file path

  • limit_similarity (Int) (defaults to: 0.9) —

    Accepting similarity (default is 90% matching)

Returns:

  • (Boolean) —

    true if matching score is higher than limit_similarity false otherwise

Raises:

  • (ArgumentError) 


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# File 'lib/image_match.rb', line 110

def perfect_match(image1_filename, image2_filename, limit_similarity=0.9)
  raise ArgumentError, 'File does not exists.' unless File.exist?(image1_filename) and File.exist?(image2_filename)
  raise ArgumentError, 'limit_similarity must be 0.1 - 1.0.' unless limit_similarity >= 0.1 and limit_similarity <= 1.0

  image1, image2 = nil, nil
  begin
    image1 = IplImage.load(image1_filename)
    image2 = IplImage.load(image2_filename)
  rescue
    raise RuntimeError, 'Couldn\'t read image files correctly'
    return false
  end

  return false unless image1.width == image2.width and image1.height == image2.height

  return perfect_match_template(image1_filename, image2_filename, limit_similarity)
end

#perfect_match_template(scene_filename, template_filename, limit_similarity = 0.9, is_output = false) ⇒ Boolean

Calculate matching score of 1st input image and 2nd input image. The 2nd input image size must be smaller than 1st input image. This function is robust for brightness.

Parameters:

  • scene_filename (String) —

    Scene image file path

  • template_filename (String) —

    template image file path which you want find in scene image

  • limit_similarity (Int) (defaults to: 0.9) —

    Accepting similarity (default is 90% matching)

  • is_output (Boolean) (defaults to: false) —

    if you set true, you can get match result with image (default is false)

Returns:

  • (Boolean) —

    true if matching score is higher than limit_similarity false otherwise

Raises:

  • (ArgumentError) 


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# File 'lib/image_match.rb', line 141

def perfect_match_template(scene_filename, template_filename, limit_similarity=0.9, is_output=false)
  raise ArgumentError, 'File does not exists.' unless File.exist?(scene_filename) and File.exist?(template_filename)
  raise ArgumentError, 'limit_similarity must be 0.1 - 1.0.' unless limit_similarity >= 0.1 and limit_similarity <= 1.0
  raise ArgumentError, 'is_output must be true or false.' unless is_output == false or is_output == true
  
  scene, template = nil, nil
  begin
    scene    = IplImage.load(scene_filename)
    template = IplImage.load(template_filename)
  rescue
    raise RuntimeError, 'Couldn\'t read image files correctly'
    return false
  end

  return false unless scene.width >= template.width and scene.height >= template.height

  result   = scene.match_template(template, :ccoeff_normed)
  min_score, max_score, min_point, max_point = result.min_max_loc

  if is_output
    from = max_point
    to = CvPoint.new(from.x + template.width, from.y + template.height)
    scene.rectangle!(from, to, :color => CvColor::Red, :thickness => 3)
    scene.save_image(Time.now.to_i.to_s + "_match_result.png")
  end

  return (max_score >= limit_similarity ? true : false)
end