Image Processing Techniques Quiz

Shaan is working on a project where he has a photograph of a landscape, but the boundaries between different elements like trees and the sky are faint and broken due to noise. He applies an edge detection algorithm to the image, but the edges appear discontinuous. To create meaningful object boundaries in his photograph, which additional processing step should he use?

• Region splitting

• Edge linking by hysteresis

• Thresholding

• Region merging

Aashi is trying to analyze a grayscale image of a landscape taken during sunset. However, the uneven lighting in the image makes simple global thresholding ineffective in separating the trees from the background. What would be a better segmentation method to handle this?

• Global thresholding

• Adaptive thresholding or region-based segmentation

• Edge detection

• Point detection

Aanya is working on a project where she needs to segment a satellite image that contains large heterogeneous areas like forests, rivers, and urban regions. By dividing the image into smaller homogeneous regions and then combining similar adjacent regions, what kind of segmentation approach is Aanya using?

• Clustering

• Edge detection

• Region splitting and merging

• Thresholding

In a photography workshop, after Kiara applies a Gaussian filter to her images for noise reduction and computes the gradient magnitude to enhance the details, what is the next step that helps her locate potential edges in her photographs?

• Edge linking

• Non-maximum suppression

• Hysteresis thresholding

• Thresholding

Why is edge detection typically preferred over point or line detection for image segmentation tasks?

• Points are easier to detect but less informative

• Edges form continuous boundaries that define object shapes better

• Lines cannot identify object boundaries

• Points give more detailed information than edges