First derivative mask such as Robert, Prewitt, Sobel and Fri-chen are suitable to detect Step EdgesSelect one:TrueFalse

Analyzing the Statement

The statement claims that first derivative masks, specifically Robert, Prewitt, Sobel, and Fritsch, are suitable for detecting step edges. This relates to edge detection in image processing, where first derivative filters are used to identify rapid changes in intensity, indicative of an edge.

1. Understanding First Derivative Masks:

   • Roberts: Utilizes a 2x2 kernel that calculates the gradient of the image intensity to detect edges.
   • Prewitt: Employs a 3x3 kernel to compute the gradient magnitude in both vertical and horizontal directions.
   • Sobel: Similar to Prewitt but emphasizes larger gradients more effectively with weighted kernels.
   • Fritsch: Refers to a technique similar to Sobel which operates under the first derivative concept.

2. Edge Detection Capability:

   • All four masks are designed to highlight areas where there is a sharp transition in pixel values, which is characteristic of step edges.

Conclusion

Given the characteristics of these masks, they are indeed suitable for detecting step edges in images.

Final Answer

True. First derivative masks like Roberts, Prewitt, Sobel, and Fritsch are suitable for detecting step edges.