Introduction to Computer Vision

What is the aim of Computer Vision (CV)?

• To enable machines to interpret visual information

• To enhance image quality

• To perform pixel-level manipulation

• To analyze biological images

What does Image Processing (IP) focus on?

• Interpreting visual information

• Transforming and analyzing images

• Object detection

• Facial recognition

What is the difference between CV and IP?

• CV focuses on pixel-level manipulation

• IP works on higher-level interpretation

• CV is more focused on higher-level interpretation

• IP allows for applications like object detection

What are the basic operations in image processing?

• Image acquisition, preprocessing, enhancement

• Filtering, noise reduction, color adjustments

• Object detection, facial recognition

• Segmentation, feature extraction

What is edge detection used for?

• Identifying boundaries in images

• Enhancing image quality

• Segmenting images into regions

• Extracting features from images

What is the purpose of segmentation in image processing?

• Dividing an image into meaningful regions

• Identifying boundaries

• Enhancing image quality

• Extracting features

What is a common application of computer vision in healthcare?

• Medical imaging for diagnosing diseases

• Image-based product search

• Facial recognition in security systems

• Augmented reality for virtual try-ons

What is the role of computer vision in self-driving cars?

• Lane detection and object recognition

• Image enhancement

• Facial recognition

• Medical imaging

What is the function of OCR software?

• Enhancing scanned documents

• Recognizing text in images

• Detecting faces

• Segmenting images

What are the three types of images?

• Binary, grayscale, color

• Monochrome, color, RGB

• Black and white, color, sepia

• Vector, raster, 3D