Which process is responsible for converting an image into a binary format, and which edge detection algorithm is commonly used in digital image processing?

Correct option is D

Thresholding is the process responsible for converting a grayscale image into a binary format by setting a threshold value. Pixels with intensity above the threshold are set to one value (e.g., white), and pixels below the threshold are set to another (e.g., black). The Canny edge detection algorithm is a widely used method in digital image processing for detecting edges. It is known for its accuracy and multi-step process, including noise reduction, gradient detection, and edge tracking.
Important Key Points
1. Thresholding:
· Converts grayscale images into binary images.
· Uses a threshold value to classify pixel intensities as either foreground or background.
· Commonly used in applications like image segmentation and OCR (Optical Character Recognition).
2. Canny Edge Detection Algorithm: Known for detecting edges with low error rates.
· Steps:
· Gaussian Filtering: Smooths the image to reduce noise.
· Gradient Calculation: Identifies intensity gradients.
· Non-Maximum Suppression: Retains the sharpest edges.
· Double Thresholding: Classifies edges as strong or weak based on intensity.
· Edge Tracking: Connects weak edges to strong edges if they are continuous.
3. Applications:
· Object detection.
· Image segmentation.
· Feature extraction for machine learning.
Knowledge Booster
· Other Processes and Algorithms:
· Quantization: Reduces the color or intensity levels in an image.
· Sampling: Converts analog signals into discrete signals for digital processing.
· Compression: Reduces file size but does not necessarily convert to binary format.
· Other Edge Detection Algorithms:
· Laplacian: Highlights regions of rapid intensity change but is sensitive to noise.
· Sobel: Detects edges using convolution kernels for horizontal and vertical gradients.
· Prewitt: Similar to Sobel but simpler, less accurate for edge detection.
· Roberts: Efficient but highly sensitive to noise and less robust compared to Canny.