Computer Vision — Winter 2025

Define the following: 1) Pixel 2) Kernel 3) Radiometry

Explain Discrete Fourier Transform (DFT) in brief.

What is computer vision? Discuss low-level, mid-level and high-level computer vision with its applications.

What is image segmentation? Discuss various applications of image segmentation.

Discuss any two morphological operations in detail.

What do you understand by geometric 2D transformation in image formation? Explain with suitable examples.

The following input image has a size of 5 x 5 pixels, and its gray level varies from 0 to 255. Apply 3 x 3 median filter for image enhancement to the input image and provide a 5 x 5 output image matrix. Make suitable assumptions for the border pixels.

Describe watershed segmentation method in brief.

Discuss the two-dimensional wavelet decomposition with necessary figure.1

What is the use of PCA in image processing? Explain PCA in detail.

Discuss region splitting and region merging image segmentation method in brief.

Explain normalized cut method for image segmentation.

Discuss any one method for corner detection with suitable example.

Explain the motion parallax in brief.

Describe the fisheye camera model in detail.

Discuss the intrinsic and extrinsic parameters related to camera models.

Discuss pinhole imaging model in brief.

Explain radial distortion in camera calibration.

What is optical flow? Describe optical flow algorithm in motion analysis.

Explain any two methods of pixel transformation in image processing.

What is machine learning? Explain different types of machine learning methods used in computer vision.

Discuss the kalman filter for motion tracking in detail.

Describe any one method or algorithm for edge detection.

Describe appearance-based object identification methods.

What is Image classification? Discuss the use of machine learning in image classification.