Contenido del Curso
Computer Vision Course Outline
Computer Vision Course Outline
Edge Detection
Edge Detection
Edges represent sudden changes in pixel intensity, which usually correspond to object boundaries. Detecting edges helps in shape recognition and segmentation.
Sobel Edge Detection
The Sobel operator calculates gradients (changes in intensity) in both the X and Y directions, helping detect horizontal and vertical edges.
Canny Edge Detection
The Canny Edge Detector is a multi-stage algorithm that provides more accurate edges by:
- Applying Gaussian blur to remove noise.
- Finding intensity gradients using Sobel filters.
- Suppressing weak edges.
- Using double thresholding and edge tracking.
A comparison of edge detection methods:
Swipe to start coding
Your task is to apply both methods, Sobel and Canny. Steps:
- Convert photo to grayscale;
- Apply Sobel filter on X and Y directions with output depth
cv2.CV_64F
and kernel size3
; - Combine Sobel-filtered directions;
- Apply a Canny filter with a threshold from
200
to300
.
Solución
¡Gracias por tus comentarios!
Edge Detection
Edge Detection
Edges represent sudden changes in pixel intensity, which usually correspond to object boundaries. Detecting edges helps in shape recognition and segmentation.
Sobel Edge Detection
The Sobel operator calculates gradients (changes in intensity) in both the X and Y directions, helping detect horizontal and vertical edges.
Canny Edge Detection
The Canny Edge Detector is a multi-stage algorithm that provides more accurate edges by:
- Applying Gaussian blur to remove noise.
- Finding intensity gradients using Sobel filters.
- Suppressing weak edges.
- Using double thresholding and edge tracking.
A comparison of edge detection methods:
Swipe to start coding
Your task is to apply both methods, Sobel and Canny. Steps:
- Convert photo to grayscale;
- Apply Sobel filter on X and Y directions with output depth
cv2.CV_64F
and kernel size3
; - Combine Sobel-filtered directions;
- Apply a Canny filter with a threshold from
200
to300
.
Solución
¡Gracias por tus comentarios!