Computer Vision

Introduction

Bounding Box

Principal Component Analysis (PCA)

Homography & Affine

Backgroud Subtraction

Light Glare Problem

Spot Differences

Histrogram Matching

Depth Map (stereo camera)

Optical Character Recognition (OCR)

Point to Point correspondence

Object Tracking

YOLOV (the most well-known family of object detection and classification)

Study Cases

Understanding color & the in-camera image processing pipeline for computer vision

https://www.eecs.yorku.ca/~mbrown/ICCV19_Tutorial_MSBrown.pdf

![[Untitled 355.png|https://arxiv.org/abs/2202.08360]]

https://www.tutorialspoint.com/dip/index.htm

https://www.youtube.com/watch?v=cLeF-KNHgwU&ab_channel=CyrillStachniss

https://charmve.medium.com/surface-defect-detection-dataset-papers-4d0ff26dfcb7

https://github.com/josephmisiti/awesome-machine-learning#computer-vision-5

Background Subtractors: MOG vs MOG2 vs GMG vs KNN vs CNT

Marcar defeitos com cor diferente

findContours → fitEllipse

https://github.com/roboflow/supervision

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