Chap 3 : Binary Image Chap 3 : Binary Image AnalysisAnalysis
Counting Foreground Counting Foreground ObjectsObjects
ExampleExample
Counting Object AlgorithmCounting Object Algorithm
Counting Background Counting Background ObjectsObjects
Connected Component Connected Component LabelingLabeling
1. 1. Recursive Connected Recursive Connected Components AlgorithmComponents Algorithm
ExamplExamplee
2. 2. Classical Connected Classical Connected Components AlgorithmComponents Algorithm
Size FilterSize Filter
• To remove small size noise After connected component labeling, all components below T in size are removed by changing the corresponding pixels to 0.
Pepper & Salt Noise Pepper & Salt Noise ReductionReduction
• Change a pixel from 0 to 1 if all neighborhood pixels of the pixel is 1
• Change a pixel from 1 to 0 if all neighborhood pixels of the pixel is 0
Expanding & ShrinkingExpanding & Shrinking
Example 1Example 1
Example 2Example 2
MorphologicMorphological Filteral Filter
ExamplExamplee
Example Example
Closing & OpeningClosing & Opening
Opening ExampleOpening Example
MorphologicMorphological Filter al Filter Example 1Example 1
Structure Element Structure Element Example 1Example 1
MorphMorpho-o-logical logical Filter Filter ExamplExample 2e 2
Structure Element Structure Element Example 2Example 2
Conditional DilationConditional Dilation
Conditional Conditional Dilation Dilation ExampleExample
Area & CentroidArea & Centroid
PerimeterPerimeter
CircularityCircularity
Second Moment Second Moment
OrientationOrientation
Bounding BoxBounding Box
ThresholdingThresholding
P-Tile MethodP-Tile Method
Mode MethodMode Method
Mode AlgorithmMode Algorithm
Iterative MethodIterative Method
221
T
Adaptive MethodAdaptive Method
Adaptive Method ExampleAdaptive Method Example
Variable Thresholding Variable Thresholding ExampleExample
Double Thresholding Double Thresholding MethodMethod
Double Double Thresholding Thresholding ExampleExample
RecursivRecursive e HistograHistogram m ClusterinClusteringg
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