MCQs

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Overall MCQs for Reference

1. Which technique divides an image into meaningful regions or objects?
   a. Filtering
   b. Segmentation
   c. Transformation
   d. Morphological Operations
   Answer: b. Segmentationeasyexamnotes​
2. What is the goal of image segmentation?
   a. Enhance image resolution
   b. Group similar pixels for analysis
   c. Encrypt images
   d. Generate 3D models
   Answer: b. Group similar pixels for analysisgeeksforgeeks​
3. Which approach is commonly used for boundary detection in images?
   a. Thresholding
   b. Edge detection
   c. Smooth filtering
   d. Histogram equalization
   Answer: b. Edge detectionencord​
4. Region-growing segmentation is initiated using:
   a. Threshold pixels
   b. Seed pixels
   c. Edge pixels
   d. Noise pixels
   Answer: b. Seed pixelshellointern​
5. What describes ‘semantic segmentation’?
   a. Divides image into color bands
   b. Labels every pixel with a class
   c. Compresses image data
   d. Tracks objects through frames
   Answer: b. Labels every pixel with a classaionlinecourse​
6. Which technique separates pixels based on their intensity values?
   a. Region growing
   b. Thresholding
   c. Morphological filtering
   d. Edge detection
   Answer: b. Thresholdinghellointern​
7. In discontinuity-based segmentation, what is detected?
   a. Uniform patterns
   b. Sharp intensity changes
   c. Texture
   d. Color gradients
   Answer: b. Sharp intensity changesencord​
8. Which model is designed for medical image segmentation?
   a. ResNet
   b. U-Net
   c. Mask R-CNN
   d. YOLO
   Answer: b. U-Netgeeksforgeeks​
9. What is a key feature of Fully Convolutional Networks (FCN) for segmentation?
   a. Uses recurrent layers
   b. Outputs pixel-wise segmentation maps
   c. Only supports grayscale images
   d. Is unsupervised
   Answer: b. Outputs pixel-wise segmentation mapsgeeksforgeeks​
10. Which method is region-based?
    a. Canny edge detection
    b. Split and merge segmentation
    c. K-means clustering
    d. Box filtering
    Answer: b. Split and merge segmentationencord​
11. In clustering-based segmentation, which algorithm is commonly used?
    a. Gaussian blur
    b. Depth-first search
    c. K-means
    d. PCA
    Answer: c. K-meansaimcqs​
12. What is instance segmentation?
    a. Segmenting only background pixels
    b. Assigns unique labels to each object instance
    c. Classifies images globally
    d. Transforms images
    Answer: b. Assigns unique labels to each object instancegeeksforgeeks​
13. Which segmentation type assigns both semantic and instance labels?
    a. Panoptic segmentation
    b. Semantic segmentation
    c. Threshold-based segmentation
    d. Global labeling
    Answer: a. Panoptic segmentationgeeksforgeeks​
14. Which architectural feature of U-Net enables fine detail retention?
    a. Residual blocks
    b. Skip connections
    c. Batch normalization
    d. Dropout regularization
    Answer: b. Skip connectionsgeeksforgeeks​
15. What does Mask R-CNN extend for segmentation?
    a. YOLO
    b. Faster R-CNN
    c. FCN
    d. LSTM
    Answer: b. Faster R-CNNgeeksforgeeks​
16. What metric often evaluates image segmentation quality?
    a. PSNR
    b. Intersection over Union
    c. Precision-recall
    d. F1 Score
    Answer: b. Intersection over Uniongeeksforgeeks​
17. What preprocessing step enhances segmentation by reducing noise?
    a. Resizing
    b. Gaussian blur
    c. Histogram matching
    d. Sobel filtering
    Answer: b. Gaussian blurscribd​
18. Which method’s criterion is pixel similarity (intensity, color, texture)?
    a. Edge-based segmentation
    b. Region-based segmentation
    c. Morphological segmentation
    d. Frequency domain analysis
    Answer: b. Region-based segmentationencord​
19. What does the Segment Anything Model (SAM) output for a prompt?
    a. Feature map
    b. Segmentation mask
    c. Blurred image
    d. Edge-only image
    Answer: b. Segmentation maskencord​
20. Which application relies on segmentation for scene perception?
    a. Audio synthesis
    b. Autonomous vehicles
    c. Text processing
    d. Data mining
    Answer: b. Autonomous vehiclesbasic​
21. What is the main goal of morphological watershed segmentation?
    a. Color enhancement
    b. Delineate regions using topographic concepts
    c. Resize images
    d. Increase contrast
    Answer: b. Delineate regions using topographic conceptssanfoundry​
22. Which segmentation technique is effective for uniform background images?
    a. Edge detection
    b. Thresholding
    c. Region splitting
    d. Texture analysis
    Answer: b. Thresholdingencord​
23. Which backbone model is widely used in segmentation networks?
    a. ResNet
    b. AlexNet
    c. VGG
    d. LSTM
    Answer: a. ResNetgeeksforgeeks​
24. In deep learning, which loss function is used for binary mask prediction?
    a. Cross-entropy
    b. MSE
    c. Hinge loss
    d. Triplet loss
    Answer: a. Cross-entropygeeksforgeeks​
25. Which is NOT a step in classical segmentation approaches?
    a. Edge linking
    b. Feature extraction
    c. Thresholding
    d. Tokenization
    Answer: d. Tokenizationsanfoundry​
26. What does boundary-based segmentation rely on?
    a. Marker placement
    b. Edge detection
    c. Histogram equalization
    d. Image pyramids
    Answer: b. Edge detectionencord​
27. What is a possible drawback of edge-based segmentation?
    a. Works best on noisy images
    b. May struggle with homogeneous regions
    c. Ignores color channels
    d. Slow performance
    Answer: b. May struggle with homogeneous regionsencord​
28. What is the first step in most computer vision segmentation workflows?
    a. Detecting edges
    b. Applying segmentation algorithms
    c. Normalizing pixel values
    d. Splitting images into blocks
    Answer: b. Applying segmentation algorithmsstudocu​
29. Which tool automates initial segmentation using foundation models?
    a. Segment Anything Model (SAM)
    b. Histogram analysis
    c. SIFT
    d. SURF
    Answer: a. Segment Anything Model (SAM)basic​
30. Which segmentation type is most granular?
    a. Semantic segmentation
    b. Instance segmentation
    c. Panoptic segmentation
    d. Edge segmentation
    Answer: b. Instance segmentationgeeksforgeeks​
31. What property is used in similarity-based segmentation?
    a. Discontinuity
    b. Uniformity in pixels
    c. Merging clusters
    d. Edge sharpness
    Answer: b. Uniformity in pixelsencord​
32. What technique groups pixels into clusters?
    a. Edge detection
    b. K-means clustering
    c. Sobel filtering
    d. Max pooling
    Answer: b. K-means clusteringaimcqs​
33. What is the output domain for image segmentation models?
    a. Bounding boxes
    b. Pixel-wise labels
    c. Vector graphs
    d. Audio samples
    Answer: b. Pixel-wise labelsgeeksforgeeks​
34. Which edge detection algorithm is popular for segmentation?
    a. Canny
    b. Hough
    c. PCA
    d. DBSCAN
    Answer: a. Cannyencord​
35. Which class of segmentation uses only local pixel features?
    a. Region-based
    b. Edge-based
    c. Frequency-based
    d. Semantic-based
    Answer: b. Edge-basedencord​
36. Which principle guides panoptic segmentation?
    a. Compress images efficiently
    b. Label both instances and semantics
    c. Use unsupervised learning
    d. Enhance colors only
    Answer: b. Label both instances and semanticsgeeksforgeeks​
37. What does ‘watershed’ refer to in segmentation?
    a. Watermark detection
    b. Topographic surface analysis
    c. Denoising images
    d. Feature selection
    Answer: b. Topographic surface analysissanfoundry​
38. Which segmentation application is vital in medical imaging?
    a. Feature compression
    b. Tumor boundary detection
    c. Background subtraction
    d. Image resizing
    Answer: b. Tumor boundary detectiongeeksforgeeks​
39. Segmentation masks are most useful for which task?
    a. Object detection
    b. Pixel classification
    c. Color enhancement
    d. Feature scaling
    Answer: b. Pixel classificationaionlinecourse​
40. What is a common challenge in automatic segmentation?
    a. Overfitting
    b. Handling occluded objects
    c. Channel mismatches
    d. Fast GPU requirements
    Answer: b. Handling occluded objectsgeeksforgeeks​
41. What is ‘split and merge’ segmentation’s stopping criterion?
    a. No regions remain
    b. Similarity threshold reached
    c. Color balancing achieved
    d. Histogram flattened
    Answer: b. Similarity threshold reachedencord​
42. Which feature does deep learning segmentation models often extract?
    a. Edges only
    b. Semantic features
    c. Macro pixels
    d. Resized regions
    Answer: b. Semantic featuresgeeksforgeeks​
43. What describes reasoning segmentation with LISA?
    a. Segments by color only
    b. Segments and pairs results with external data
    c. Compresses images
    d. Applies random filter
    Answer: b. Segments and pairs results with external databasic​
44. What technique is used for feature-based segmentation?
    a. Histogram analysis
    b. Edge detection
    c. Feature clustering
    d. All of the above
    Answer: d. All of the aboveencord​
45. Which task benefits least from segmentation?
    a. Traffic sign recognition
    b. Image enhancement
    c. Tumor localization
    d. Person detection
    Answer: b. Image enhancementgeeksforgeeks​
46. Which segmentation method is sensitive to image noise?
    a. Thresholding
    b. Morphological watershed
    c. Edge detection
    d. Clustering
    Answer: c. Edge detectionencord​
47. Which computation is performed in Split-and-Merge segmentation?
    a. Region similarity checks
    b. Histogram flattening
    c. Frequency transformation
    d. Feature extraction only
    Answer: a. Region similarity checksencord​
48. What is a benefit of using CNNs for segmentation?
    a. Speed
    b. Ability to extract hierarchical features
    c. Reduced memory requirements
    d. Only grayscale processing
    Answer: b. Ability to extract hierarchical featuresscribd​
49. Which segmentation methodology creates a topographic map of intensity?
    a. Watershed
    b. K-means clustering
    c. Edge detection
    d. Color balancing
    Answer: a. Watershedsanfoundry​
50. What is the role of pixel-wise classification in segmentation?
    a. Lumps pixels together
    b. Assigns class label to each pixel
    c. Detects only the boundaries
    d. Resizes images
    Answer: b. Assigns class label to each pixelaionlinecourse​

1. https://easyexamnotes.com/digital-image-processing-mcqs/
2. https://www.geeksforgeeks.org/computer-vision/image-segmentation-techniques-and-applications/
3. https://encord.com/blog/image-segmentation-for-computer-vision-best-practice-guide/
4. https://hellointern.in/blog/top-interview-questions-and-answers-for-image-processing-8744
5. https://www.aionlinecourse.com/ai-quiz-questions/computer-vision/semantic-segmentation
6. https://aimcqs.com/computer-vision
7. https://www.scribd.com/document/856373304/AUTOMATED-MCQ-EVALUATION-USING-DEEP-LEARNING-AND-IMAGE-SEGMENTATION
8. https://www.basic.ai/blog-post/image-segmentation
9. https://www.sanfoundry.com/1000-digital-image-processing-questions-answers/
10. https://www.studocu.com/in/quiz/image-segmentation-digital-image-processing-unit-4/3932267
11. https://www.cliffsnotes.com/study-notes/21305581
12. https://www.scribd.com/document/475481448/Image-Processing-MCQ
13. https://wayground.com/admin/quiz/6086ea7ed757b6001b31613f/image-segmentation
14. https://www.sanfoundry.com/artificial-intelligence-mcqs-perception/
15. https://www.scribd.com/document/515070773/DIP-Unit-4-MCQ
16. https://www.watelectronics.com/mcq/digital-image-processing/
17. https://www.studocu.com/in/document/apj-abdul-kalam-technological-university/image-processing/ip-mcqs-image-processing-mcqs/16489007
18. https://openaccess.thecvf.com/content_cvpr_2015/papers/Rupprecht_Image_Segmentation_in_2015_CVPR_paper.pdf
19. https://www.scribd.com/document/544716034/58-24-SA-V1-S1-quessegmentation
20. https://www.interviewbit.com/artificial-intelligence-mcq/