Computer Vision MCQs December 22, 2025August 9, 2024 by u930973931_answers 32 min Score: 0 Attempted: 0/32 Subscribe 1. What is the primary goal of computer vision? (A) To create software that can process natural language (B) To build efficient databases for large-scale data storage (C) To develop algorithms for data encryption (D) To enable machines to interpret and understand visual information from the world 2. Which of the following is a common application of computer vision? (A) Text classification (B) Image recognition (C) Speech synthesis (D) Data compression 3. In computer vision, what does the term âobject detectionâ refer to? (A) Identifying the type of an object within an image (B) Analyzing the sentiment of a text (C) Converting text into speech (D) Finding and locating objects within an image 4. Which algorithm is commonly used for object detection? (A) Support Vector Machines (SVM) (B) Principal Component Analysis (PCA) (C) K-Means Clustering (D) Convolutional Neural Networks (CNNs) 5. What is the purpose of the âConvolutional Layerâ in a CNN? (A) To extract features from the input image (B) To perform downsampling (C) To merge multiple features (D) To flatten the input data 6. Which of the following techniques is used for image classification? (A) Support Vector Machines (SVM) (B) Scale-Invariant Feature Transform (SIFT) (C) Histogram of Oriented Gradients (HOG) (D) Optical Character Recognition (OCR) 7. What does âSegmentationâ refer to in computer vision? (A) Dividing an image into multiple segments or regions (B) Identifying the main object in an image (C) Extracting features from an image (D) Classifying objects in an image 8. Which model architecture is known for its deep layers and is commonly used in computer vision tasks? (A) Decision Trees (B) Random Forest (C) K-Nearest Neighbors (KNN) (D) Convolutional Neural Networks (CNNs) 9. What is âImage Augmentationâ used for? (A) To decrease the number of images in a dataset (B) To increase the size of the dataset by creating modified versions of images (C) To perform feature extraction (D) To merge multiple images into one 10. Which of the following is a common dataset used for training image classification models? (A) IMDB (B) MNIST (C) UCI Machine Learning Repository (D) Yelp Reviews 11. In computer vision, what does âFeature Extractionâ involve? (A) Identifying the class of objects in an image (B) Converting images into numerical features that can be used for machine learning (C) Segmenting an image into different regions (D) Detecting the presence of objects in an image 12. Which technique is used to detect edges in an image? (A) Gaussian Blur (B) Histogram Equalization (C) Sobel Operator (D) Hough Transform 13. What is âObject Trackingâ in computer vision? (A) Identifying objects in an image (B) Segmenting objects within an image (C) Classifying objects into categories (D) Following the movement of an object across a series of frames 14. Which of the following is used for detecting and recognizing faces in images? (A) Hough Transform (B) Linear Discriminant Analysis (LDA) (C) K-Means Clustering (D) Haar Cascades 15. What does âDepth Perceptionâ refer to in computer vision? (A) Extracting features from an image (B) Detecting the color of objects in an image (C) Identifying the type of objects in an image (D) Estimating the distance of objects from the camera 16. What is âSemantic Segmentationâ? (A) Combining different segments of an image into one (B) Detecting and locating objects within an image (C) Classifying each pixel in an image into predefined categories (D) Performing image classification 17. Which algorithm is used for object recognition and localization? (A) YOLO (You Only Look Once) (B) K-Means Clustering (C) Linear Regression (D) Principal Component Analysis (PCA) 18. What is the purpose of âTransfer Learningâ in computer vision? (A) Extracting features from raw image data (B) Generating new images from existing ones (C) Using pre-trained models on new but similar tasks (D) Performing dimensionality reduction 19. Which of the following techniques is used for image denoising? (A) Histogram Equalization (B) Gaussian Blur (C) Edge Detection (D) Image Segmentation 20. In the context of CNNs, what is âPoolingâ used for? (A) Reducing the spatial dimensions of an image (B) Increasing the resolution of an image (C) Normalizing the pixel values of an image (D) Enhancing the contrast of an image 21. What does âOptical Character Recognition (OCR)â do? (A) Detects and tracks objects in video sequences (B) Converts images of text into machine-encoded text (C) Segments an image into different regions (D) Classifies objects in an image 22. Which of the following is used to correct lens distortion in images? (A) Calibration (B) Segmentation (C) Feature Matching (D) Depth Estimation 23. What is âHistogram of Oriented Gradients (HOG)â used for? (A) Reducing the dimensionality of data (B) Detecting edges in an image (C) Performing image segmentation (D) Extracting features for object detection 24. What is the function of âColor Space Transformationâ in image processing? (A) Enhancing image resolution (B) Extracting edges from an image (C) Converting an image from one color space to another (D) Normalizing image brightness 25. Which of the following methods is used for image registration? (A) Matching features between images (B) Performing object detection (C) Classifying objects within an image (D) Segmenting images into regions 26. In computer vision, what is âFeature Matchingâ? (A) Tracking objects over time (B) Classifying the type of objects in an image (C) Comparing features between different images to find correspondences (D) Enhancing the quality of images 27. What does â3D Reconstructionâ involve? (A) Segmenting objects within an image (B) Converting images into grayscale (C) Extracting features from an image (D) Creating a three-dimensional model from two-dimensional images 28. Which of the following is a common technique for image segmentation? (A) Principal Component Analysis (PCA) (B) Hough Transform (C) K-Means Clustering (D) Gaussian Mixture Models (GMM) 29. What is âImage Stitchingâ? (A) Extracting features from an image (B) Identifying objects in an image (C) Segmenting an image into different regions (D) Combining multiple images to create a single panoramic image 30. Which model is designed for handling temporal sequences in computer vision? (A) Recurrent Neural Networks (RNNs) (B) Decision Trees (C) Support Vector Machines (SVMs) (D) Random Forests 31. What is the purpose of âSemantic Segmentationâ? (A) Labeling each pixel in an image with a class (B) Detecting and locating objects in an image (C) Extracting features from images (D) Identifying the edges in an image 32. What does âImage Super-Resolutionâ aim to achieve? (A) Reducing the resolution of an image (B) Increasing the resolution of an image (C) Enhancing image contrast (D) Performing image segmentation