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Feature Matching (SIFT, SURF, ORB) — MCQs | Digital Image Processing

1. What does SIFT stand for in image processing?

(A) Scale-Invariant Feature Transform


(B) Scale Information Fourier Transform


(C) Simple Invariant Feature Tracking


(D) Scale Interpolation Fourier Technique



2. Which of the following is a key advantage of the SIFT algorithm?

(A) Sensitive to illumination


(B) Rotation invariance


(C) Low computational cost


(D) Requires color images



3. What type of features does SURF primarily detect?

(A) Edges


(B) Keypoints


(C) Histograms


(D) Color blobs



4. What is the full form of SURF in the context of feature detection?

(A) Simple Uniform Region Filtering


(B) Speeded Up Robust Features


(C) Scale Unified Robust Functions


(D) Surface Uniform Rotated Features



5. Which feature matching method is best suited for real-time applications due to its speed?

(A) SIFT


(B) SURF


(C) ORB


(D) BRIEF



6. What does ORB combine from other methods?

(A) SIFT and SURF


(B) FAST and BRIEF


(C) Gabor and HOG


(D) LBP and GLCM



7. Which method is not free for commercial use without a license?

(A) SIFT


(B) ORB


(C) BRIEF


(D) FAST



8. Which characteristic is shared by all SIFT, SURF, and ORB?

(A) Color dependency


(B) Rotation invariance


(C) Only works on grayscale images


(D) Requires labeled datasets



9. Why is ORB considered a good alternative to SIFT and SURF?

(A) It is less accurate


(B) It is faster and free


(C) It uses more memory


(D) It works only on color images



10. What does the FAST algorithm detect?

(A) Curved edges


(B) Corners


(C) Blobs


(D) Shapes



11. In feature matching, what does “descriptor” refer to?

(A) Region name


(B) Image format


(C) Numerical representation of a keypoint


(D) Color value



12. What is the primary step in SIFT after detecting scale-space extrema?

(A) Keypoint localization


(B) Edge detection


(C) Gradient smoothing


(D) Histogram normalization



13. SURF approximates which mathematical operation to speed up processing?

(A) Gaussian derivative


(B) Fourier transform


(C) Sobel operator


(D) Hough transform



14. Which of the following is binary descriptor based?

(A) SIFT


(B) SURF


(C) ORB


(D) Harris



15. Which one of these algorithms is scale-invariant?

(A) Harris corner detector


(B) FAST


(C) ORB


(D) SIFT



16. Which feature detection method is least computationally expensive?

(A) SIFT


(B) SURF


(C) ORB


(D) HOG



17. What is the function of a descriptor in feature matching?

(A) Filters noise


(B) Matches pixels


(C) Encodes keypoint information


(D) Tracks object shape



18. Which algorithm uses integral images for speed optimization?

(A) SIFT


(B) ORB


(C) SURF


(D) FAST



19. How are ORB descriptors represented?

(A) Floating-point vectors


(B) Integer arrays


(C) Binary strings


(D) RGB tuples



20. Which of the following is NOT a step in SIFT?

(A) Scale-space extrema detection


(B) Keypoint localization


(C) Binary pattern encoding


(D) Descriptor generation



21. Why is ORB more suitable for embedded systems?

(A) Higher memory requirement


(B) Simple color handling


(C) Lightweight and fast


(D) GPU requirement



22. Which method uses Laplacian of Gaussian (LoG) for scale-space representation?

(A) SIFT


(B) ORB


(C) SURF


(D) FAST



23. What is the goal of feature matching in image processing?

(A) Edge detection


(B) Identify identical features across images


(C) Color segmentation


(D) Histogram equalization



24. Which step in SIFT helps in achieving rotation invariance?

(A) Gradient magnitude computation


(B) Dominant orientation assignment


(C) Color normalization


(D) Edge suppression



25. Which of the following does NOT belong to keypoint detectors?

(A) SIFT


(B) SURF


(C) ORB


(D) Histogram equalization



26. In ORB, what is the purpose of BRIEF?

(A) Detects scale


(B) Describes keypoints


(C) Enhances contrast


(D) Detects edges



27. Which algorithm introduced orientation compensation in binary descriptors?

(A) ORB


(B) FAST


(C) SURF


(D) Harris



28. Which of these algorithms is least robust to image noise?

(A) SIFT


(B) ORB


(C) SURF


(D) HOG



29. In SIFT, what is used to assign orientation to keypoints?

(A) Color intensity


(B) Gradient histogram


(C) RGB values


(D) Wavelet transform



30. What is the final step in SIFT pipeline?

(A) Keypoint localization


(B) Descriptor matching


(C) Descriptor generation


(D) Orientation assignment



31. Which descriptor is most memory efficient?

(A) SIFT


(B) SURF


(C) ORB


(D) Gabor



32. What type of matching is typically used with binary descriptors?

(A) Cross-correlation


(B) Hamming distance


(C) Euclidean distance


(D) Mahalanobis distance



33. Which technique is known for both speed and rotation invariance?

(A) FAST


(B) ORB


(C) BRIEF


(D) Sobel



34. Which of the following works poorly with scale changes?

(A) SIFT


(B) SURF


(C) FAST


(D) ORB



35. What does the acronym FAST stand for?

(A) Feature Across Similar Transitions


(B) Features from Accelerated Segment Test


(C) Filtered Active Smoothing Technique


(D) Fourier Algorithm for Spatial Transformation



36. Which one is not a descriptor but a detector?

(A) SIFT


(B) SURF


(C) FAST


(D) ORB



37. Which algorithm is inspired by human vision?

(A) SIFT


(B) ORB


(C) HOG


(D) SURF



38. Which method uses Difference of Gaussians (DoG)?

(A) SURF


(B) SIFT


(C) ORB


(D) BRIEF



39. Which one is more suitable for low-power devices?

(A) SIFT


(B) ORB


(C) SURF


(D) HOG



40. Which library includes ORB as a standard feature detector?

(A) TensorFlow


(B) PyTorch


(C) OpenCV


(D) Keras



41. What does keypoint orientation help in achieving?

(A) Faster rendering


(B) Rotation invariance


(C) Scale reduction


(D) Edge sharpening



42. What is the common descriptor vector size for SIFT?

(A) 32


(B) 64


(C) 128


(D) 256



43. Which method is most resistant to image transformations?

(A) SIFT


(B) BRIEF


(C) FAST


(D) ORB



44. What is the drawback of BRIEF?

(A) High memory usage


(B) Poor rotation invariance


(C) Poor matching speed


(D) Color dependency



45. Which method uses a Hessian matrix for detection?

(A) ORB


(B) SURF


(C) SIFT


(D) BRIEF



46. Which of the following descriptors is most compact?

(A) SIFT


(B) SURF


(C) ORB


(D) Gabor



47. Which algorithm is NOT suitable for real-time applications due to complexity?

(A) ORB


(B) SIFT


(C) BRIEF


(D) FAST



48. What is the typical application of feature matching?

(A) Color balance


(B) Image compression


(C) Object recognition


(D) Noise filtering



49. Which algorithm uses Gaussian smoothing?

(A) SIFT


(B) ORB


(C) BRIEF


(D) FAST



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