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Techniques of Edge Detection, ANGEL OCTAVIO RAMOS JIMÉNEZ, TRATAMIENTO DE…
Techniques of Edge Detection
Fist Derivate
Roberts
Advantages
Good at Detecting
Horizontal and Vertical Edges
Simple and fast for calculations
Good location
Disadvantages
Bad at detecting
Diagonal Edges
Sensitive to noise
Use of small masks
Lack of information
About Edges Orientation
Wide egdes
Multiple pixels
Masks
Sobel
Disadvantages
Slow calculations
Bad at detecting
Diagonal Edges
Lack of information
About Edges Orientation
Wide egdes
Multiple pixels
Masks
Advantages
Low sensitivity to noise
Use of masks of different sizes
Good at Detecting
Horizontal and Vertical Edges
Prewitt
Disadvantages
Bad at detecting
Diagonal Edges
Wide egdes
Multiple pixels
Slow calculations
Masks
Advantages
Low sensitivity to noise
Good at Detecting
Horizontal and Vertical Edges
Provides the Magnitude and Direction of the Edge
Uses the Gradient Operator
Uses masks
Canny
Detection of Finer Edges
Use of different thresholds
It can detect
Strong edges
Weak edges
Use the magnitude and direction
Gradient vector
Removes maximums from noise
Avoiding false edges
Second Derivate
Used in edge detection
independent of orientation
Uses the Laplacian Operator
Uses masks
Used in a continuous function
Funtion f(x,y)
Advantages
Optimal Width Edges
Good at Detecting
Horizontal and Vertical Edges
Diagonal Edges
Good location
Disadvantages
Sensitive to noise
Detection of False Edges
Masks
GRADIENT
Detects changes of the gray levels
In reduced regions
It's a vector
Funtion f(x,y)
Gradient formula
Magnitude
Edge Force
Formula
ANGEL OCTAVIO RAMOS JIMÉNEZ
TRATAMIENTO DE IMÁGENES
LUIS ENRIQUE LEDEZMA FUENTES
UNIVERSIDAD AUTÓNOMA DEL ESTADO DE MÉXICO
FACULTAD DE INGENIERÍA
22-10-2020
