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

51
Score: 0
Attempted: 0/51
Subscribe
1. What does HSV stand for in color space conversion?



2. Which of the following is not a component of the HSI color space?



3. In the HSV model, which component represents the color type?



4. In YCbCr, what does the ‘Y’ component represent?



5. Which color space separates intensity from color information?



6. Which of the following color models is most commonly used in image processing for compression?



7. What is the main advantage of converting RGB to HSV?



8. Which color space uses cylindrical coordinates?



9. In the RGB color space, each color is a combination of:



10. What is the typical range of the ‘Hue’ component in HSV color space?



11. Which color space is often used in television broadcasting?



12. In which color model is Intensity calculated as the average of RGB components?



13. Which of the following components in YCbCr contains most of the image details?



14. The ‘Saturation’ in HSI refers to:



15. Which transformation is nonlinear in RGB to HSV conversion?



16. Which color space provides a more human-perceptual color representation?



17. In HSI, the intensity component is influenced by:



18. In YCbCr, what do Cb and Cr represent?



19. Which of the following is device-dependent?



20. Why is YCbCr preferred in compression techniques?



21. What does chrominance describe in color models?



22. Which component in HSI is angular?



23. RGB is considered what type of color model?



24. What happens to RGB values in a grayscale image?



25. Which color model is most intuitive for human color perception?



26. Which of the following models is based on human visual sensitivity?



27. Which component of HSV defines the brightness of color?



28. In the RGB to HSV conversion, which component remains constant when brightness changes?



29. In image processing, the conversion from RGB to YCbCr is mostly used for:



30. Which component of HSV determines how much gray is in the color?



31. How is Y calculated in the YCbCr model?



32. In YCbCr, which component is most affected by lighting conditions?



33. Which of the following is a drawback of the RGB model in image processing?



34. Which of the following models is best for edge detection in colored images?



35. Which component in HSV is related to the vividness of the color?



36. What is the main application of HSI in image analysis?



37. Which transformation results in better visual contrast in compression?



38. Which model has better chrominance separation?



39. What kind of transformation is RGB to HSI considered?



40. Which of these models allows filtering based on brightness only?



41. How does the human eye respond to brightness and color in YCbCr?



42. Which of these models is closer to the way humans describe colors?



43. What is the range of Cb and Cr in 8-bit digital images?



44. Why is RGB not preferred for segmentation?



45. How is ‘Value’ calculated in HSV?



46. Which model simplifies object detection in color images?



47. Which conversion is used in skin detection algorithms?



48. The hue component in HSV is undefined when:

50. What is the typical bit-depth of each component in YCbCr for 8-bit images?



51. Which color model is preferred for histogram equalization of color images?



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