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Template Matching — MCQs | Digital Image Processing

1. What is the main objective of template matching in image processing?

(A) Enhance image resolution


(B) Find occurrences of a template in an image


(C) Convert image to binary


(D) Compress the image



2. Which metric is commonly used to evaluate similarity in template matching?

(A) Euclidean distance


(B) Mean filter


(C) Normalized cross-correlation


(D) Fourier transform



3. Which method improves template matching by accounting for brightness variations?

(A) Histogram equalization


(B) Gaussian blur


(C) Normalized correlation coefficient


(D) Laplacian filter



4. Which of the following is a disadvantage of basic template matching?

(A) It is invariant to scale


(B) It is fast in all scenarios


(C) It is sensitive to rotation and scale


(D) It enhances edges



5. What is the typical shape of a template used in template matching?

(A) Circle


(B) Arbitrary shape


(C) Rectangular


(D) Spherical



6. Which domain is usually used for simple template matching?

(A) Frequency domain


(B) Compressed domain


(C) Spatial domain


(D) Time domain



7. What is the result of the template matching process?

(A) A binary image


(B) A histogram


(C) A similarity map


(D) A threshold image



8. Which technique allows for rotation-invariant template matching?

(A) Use of fixed template


(B) Scale normalization


(C) Template rotation at multiple angles


(D) Mean subtraction



9. Which of the following improves robustness in template matching?

(A) Thresholding


(B) Blurring


(C) Normalization


(D) Cropping



10. Template matching works best when:

(A) Objects vary in scale and orientation


(B) Object appearances are consistent


(C) The background is dynamic


(D) Images are noisy



11. Which is a limitation of using raw intensity for template matching?

(A) High accuracy


(B) Rotation invariance


(C) Sensitivity to illumination changes


(D) Less memory usage



12. Which matching metric is most sensitive to lighting changes?

(A) Mean squared error


(B) Normalized cross-correlation


(C) Structural similarity index


(D) Mutual information



13. In template matching, what is a typical size relationship between the template and the input image?

(A) Template is larger


(B) Template is same size


(C) Template is smaller


(D) No fixed relationship



14. Which operation is performed to slide the template over the image?

(A) Rotation


(B) Translation


(C) Filtering


(D) Segmentation



15. How is template matching affected by noise in the image?

(A) It becomes faster


(B) It becomes more accurate


(C) It is not affected


(D) It may produce false matches



16. What is the main alternative to template matching for object detection?

(A) Histogram matching


(B) Edge linking


(C) Feature-based matching


(D) Thresholding



17. Template matching is considered a:

(A) Feature-based method


(B) Region-growing method


(C) Dense matching technique


(D) Global matching technique



18. Which technique improves template matching by handling different scales?

(A) Histogram equalization


(B) Multi-scale pyramid


(C) Thresholding


(D) Mean filtering



19. Which measure in template matching gives the lowest value for a best match?

(A) Mean squared error


(B) Cross-correlation


(C) Normalized correlation


(D) Histogram similarity



20. Which template matching method is least affected by changes in contrast?

(A) Cross-correlation


(B) Normalized cross-correlation


(C) Euclidean distance


(D) Structural similarity index



21. Which feature of an object must remain constant for effective template matching?

(A) Color


(B) Size


(C) Shape


(D) Illumination



22. What is the effect of increasing template size in matching?

(A) More noise sensitivity


(B) Less computational cost


(C) Reduced detection accuracy


(D) More context captured



23. In normalized cross-correlation, values range between:

(A) -1 to +1


(B) 0 to 255


(C) 0 to 1


(D) -255 to +255



24. Why is template matching considered computationally expensive?

(A) Due to matrix inversion


(B) Due to Fourier transforms


(C) Due to exhaustive sliding


(D) Due to edge detection



25. Which function in most image processing libraries performs template matching?

(A) matchTemplate


(B) findContours


(C) blurImage


(D) calcHist



26. Which property of the image must match the template for accurate detection?

(A) Pixel depth


(B) Scale and orientation


(C) Mean brightness


(D) Histogram range



27. What is the primary application of template matching?

(A) Image compression


(B) Motion estimation


(C) Object detection


(D) Noise removal



28. Which of the following can help detect rotated templates?

(A) Zero padding


(B) Template flipping


(C) Rotating the template at multiple angles


(D) Erosion



29. Which algorithm can accelerate template matching?

(A) RANSAC


(B) Fast Fourier Transform


(C) Otsu’s method


(D) K-means clustering



30. Which of the following is a local matching method?

(A) Template matching


(B) Feature descriptor matching


(C) Cross correlation


(D) Histogram equalization



31. In template matching, what causes poor results in cluttered backgrounds?

(A) Brightness shift


(B) Scale change


(C) Lack of distinctiveness


(D) Large kernel size



32. Which domain approach is better for real-time matching?

(A) Spatial domain


(B) Frequency domain


(C) Compressed domain


(D) Histogram domain



33. What happens when a poor threshold is chosen in similarity map?

(A) Only exact matches are found


(B) No match is detected


(C) False positives increase


(D) Results are unaffected



34. Which image transformation can help template matching under perspective change?

(A) Log transformation


(B) Histogram stretching


(C) Affine transformation


(D) Box filtering



35. Template matching is best suited for which type of pattern recognition?

(A) Dynamic


(B) Real-time


(C) Static and known


(D) Noisy and unclear



36. Which is the simplest method for measuring difference in matching?

(A) Cosine similarity


(B) Structural similarity


(C) Sum of squared differences


(D) Homography



37. Which pre-processing step can improve matching accuracy?

(A) Image segmentation


(B) Image enhancement


(C) Image subtraction


(D) Image sampling



38. What is the effect of downsampling the image before matching?

(A) Improved accuracy


(B) Reduced accuracy


(C) Faster matching


(D) Lossless compression



39. What is an advantage of template matching over feature-based methods?

(A) Rotation invariance


(B) Simpler implementation


(C) High accuracy in all conditions


(D) Works with dynamic objects



40. Which value of normalized cross-correlation indicates a perfect match?

(A) 0


(B) 1


(C) -1


(D) 255



41. Why does template matching fail in scale-variant images?

(A) Template changes


(B) Object color differs


(C) Object becomes unrecognizable


(D) Fixed-size template doesn’t match scaled objects



42. Which interpolation method is often used while resizing a template?

(A) Nearest neighbor


(B) Linear


(C) Bicubic


(D) All of the above



43. Which of the following is a non-parametric matching method?

(A) Template matching


(B) SVM


(C) K-NN


(D) PCA



44. Which component does template matching rely on most?

(A) Shape structure


(B) Color histogram


(C) Texture


(D) Image edges



45. Which condition improves detection performance in template matching?

(A) Busy background


(B) Poor lighting


(C) High contrast object


(D) Scale variance



46. In practical applications, template matching is best used when:

(A) Object changes frequently


(B) Object is small and similar to many others


(C) Object is unique and fixed in view


(D) Background is dynamic



47. Which method allows for scale-invariant matching?

(A) Normalization


(B) Multiscale template generation


(C) Sharpening


(D) Cropping



48. Which of the following best describes template matching?

(A) Data clustering algorithm


(B) Binary segmentation method


(C) Pattern recognition technique


(D) Compression algorithm



49. What kind of object movement invalidates template matching?

(A) Translation


(B) Occlusion


(C) Fixed rotation


(D) Scaling with fixed center



50. Which matching technique uses pixel-wise comparison between a template and subregions of the input image?

(A) Template matching


(B) Region growing


(C) Edge detection


(D) Morphological filtering



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