Morphological Operations (Erosion, Dilation, Opening, Closing) — MCQs | Digital Image Processing

50
Score: 0
Attempted: 0/50
Subscribe
1. Who introduced the concept of erosion in morphological image processing?



2. What operation is used to shrink the boundaries of foreground regions in a binary image?



3. Which morphological operation is primarily used to grow or thicken objects in a binary image?



4. Which operation is defined as erosion followed by dilation?



5. What is the result of applying dilation followed by erosion?



6. Which morphological operation helps in removing small objects or noise from the foreground?



7. Which operation is suitable for filling small holes or gaps in objects?



8. Which of the following is not a basic morphological operation?



9. In dilation, what happens to the white (foreground) regions?



10. Which operation is used when we want to eliminate thin protrusions from objects?



11. What is the role of the structuring element in morphological operations?



12. What is the typical shape used for structuring elements?



13. Which of the following is used to smooth the contour of objects?



14. What is the effect of erosion on isolated pixels in a binary image?



15. Which morphological operation is used to highlight boundaries of objects?



16. In closing operation, the dilation step is followed by:



17. Which operation is used to bridge narrow breaks and long thin gulfs?



18. What happens when erosion is applied repeatedly?



19. What is the dual operation of opening?



20. Which operation helps to remove background noise while preserving the shape of objects?



21. Which combination can be used to remove noise and fill holes simultaneously?



22. Which morphological operation is more sensitive to small structures?



23. What is the basic requirement for performing morphological operations?



24. Which operation is most suitable for extracting thin lines?



25. Which of the following is not an effect of dilation?



26. What happens if erosion is applied to the background instead of the foreground?



27. What is the output of opening on an image with small bright spots and large dark regions?



28. What is a primary application of morphological operations?



29. What is the effect of increasing the size of the structuring element during dilation?



30. Which operation would most likely disconnect thin joints between objects?



31. Which operation is defined as the difference between dilation and erosion?



32. Which of the following operations is not used for pre-processing?



33. Which operation is effective in removing salt noise from a binary image?



34. Which operation is best to remove pepper noise from a binary image?



35. Which sequence of operations is applied in the closing method?



36. Which is true about morphological operations?



37. The main goal of opening is to:



38. What is a hit-or-miss operation used for?



39. Which operation would best highlight cracks or thin lines in material images?



40. A typical application of closing is:



41. Which of the following does not require a structuring element?



42. Which morphological operation can disconnect objects connected by thin lines?



43. Which morphological operation is suitable for extracting boundaries?



44. The combination of dilation and erosion results in:



45. The term “morphology” in image processing is derived from:



46. Which operation does not generally change the overall shape but removes minor protrusions?



47. Which of the following combinations improves both small noise removal and gap filling?



48. What happens to holes inside objects after closing?



49. Which operation is best for removing small black spots in white foreground?



50. What is the main idea behind using morphological operations in image processing?



More MCQs on Digital image Processing

  1. Introduction to DIP — MCQs | Digital Image Processing

  2. Human Visual System (HVS) — MCQs | Digital Image Processing

  3. Image Acquisition Devices — MCQs | Digital Image Processing

  4. Image Sampling & Quantization — MCQs | Digital Image Processing

  5. Image Resolution & Bit Depth — MCQs | Digital Image Processing

  6. Basic Image Operations (Negative, Log, Power-law) — MCQs | Digital Image Processing

  7. Histogram Equalization & Specification — MCQs | Digital Image Processing

  8. Contrast Stretching — MCQs | Digital Image Processing

  9. Image Arithmetic (Add, Subtract, Multiply, Divide) — MCQs | Digital Image Processing

  10. Bit-plane Slicing — MCQs | Digital Image Processing

  11. Smoothing Filters (Mean, Gaussian, Median) — MCQs | Digital Image Processing

  12. Sharpening Filters (Laplacian, Gradient) — MCQs | Digital Image Processing

  13. High-Boost Filtering — MCQs | Digital Image Processing

  14. Edge Detection (Sobel, Prewitt, Roberts, Canny, LoG) — MCQs | Digital Image Processing

  15. Fourier Transform (DFT, FFT) — MCQs | Digital Image Processing

  16. Frequency Domain Filtering — MCQs | Digital Image Processing

  17. Low-pass & High-pass Filters — MCQs | Digital Image Processing

  18. Homomorphic Filtering — MCQs | Digital Image Processing

  19. Noise Models (Gaussian, Salt & Pepper, Speckle) — MCQs | Digital Image Processing

  20. Adaptive Filtering — MCQs | Digital Image Processing

  21. Inverse & Wiener Filtering — MCQs | Digital Image Processing

  22. Pseudo-color & True-color Processing — MCQs | Digital Image Processing

  23. Color Space Conversion (RGB ↔ HSV, HSI, YCbCr) — MCQs | Digital Image Processing

  24. Color Image Enhancement — MCQs | Digital Image Processing

  25. Image Segmentation (Thresholding, Otsu, K-means, Region Growing) — MCQs | Digital Image Processing

  26. Edge-based Segmentation — MCQs | Digital Image Processing

  27. Region Splitting and Merging — MCQs | Digital Image Processing

  28. Watershed Algorithm — MCQs | Digital Image Processing

  29. Morphological Operations (Erosion, Dilation, Opening, Closing) — MCQs | Digital Image Processing

  30. Boundary Extraction — MCQs | Digital Image Processing

  31. Skeletonization — MCQs | Digital Image Processing

  32. Connected Components Labeling — MCQs | Digital Image Processing

  33. Texture Analysis (GLCM, LBP, Gabor Filters) — MCQs | Digital Image Processing

  34. Shape Descriptors (Perimeter, Area, Compactness, Eccentricity) — MCQs | Digital Image Processing

  35. Statistical Features (Mean, Variance, Skewness) — MCQs | Digital Image Processing

  36. Principal Component Analysis (PCA) — MCQs | Digital Image Processing

  37. Linear Discriminant Analysis (LDA) — MCQs | Digital Image Processing

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

  39. Image Registration — MCQs | Digital Image Processing

  40. Image Stitching — MCQs | Digital Image Processing

  41. Motion Detection & Optical Flow — MCQs | Digital Image Processing

  42. Background Subtraction — MCQs | Digital Image Processing

  43. Object Detection & Tracking — MCQs | Digital Image Processing

  44. Template Matching — MCQs | Digital Image Processing

  45. Pattern Recognition (KNN, SVM, ANN) — MCQs | Digital Image Processing

  46. Image Classification — MCQs | Digital Image Processing

  47. Image Clustering — MCQs | Digital Image Processing

  48. Image Compression (RLE, Huffman, LZW, JPEG, JPEG2000) — MCQs | Digital Image Processing

  49. Video Compression (MPEG, H.264) — MCQs | Digital Image Processing

  50. Image Fusion (Pixel, Feature, Decision Level) — MCQs | Digital Image Processing

  51. Image Watermarking — MCQs | Digital Image Processing

  52. Steganography — MCQs | Digital Image Processing

  53. Face Detection & Recognition — MCQs | Digital Image Processing

  54. Gesture Recognition — MCQs | Digital Image Processing

  55. 3D Image Processing — MCQs | Digital Image Processing

  56. Stereo Vision & Depth Estimation — MCQs | Digital Image Processing

  57. Medical Image Analysis (CT, MRI, Ultrasound) — MCQs | Digital Image Processing

  58. Remote Sensing Image Processing — MCQs | Digital Image Processing

  59. Satellite Image Enhancement — MCQs | Digital Image Processing

  60. Deep Learning for Image Processing (CNN, GANs, Autoencoders) — MCQs | Digital Image Processing

  61. Image Captioning — MCQs | Digital Image Processing

  62. Semantic & Instance Segmentation (Mask R-CNN, U-Net) — MCQs | Digital Image Processing

  63. Super Resolution (SRCNN, ESRGAN) — MCQs | Digital Image Processing

  64. Image Inpainting — MCQs | Digital Image Processing

  65. Image Style Transfer — MCQs | Digital Image Processing

  66. Real-Time Image Processing — MCQs | Digital Image Processing

  67. Augmented Reality (AR) & Virtual Reality (VR) — MCQs | Digital Image Processing

  68. DIP using MATLAB/OpenCV/Python — MCQs | Digital Image Processing

  69. DIP in IoT & Embedded Systems — MCQs | Digital Image Processing

  70. Ethics & Privacy in Image Processing — MCQs | Digital Image Processing

Computer Science Repeated MCQs Book Download

Related Posts:

Contents Copyrights Reserved By T4Tutorials