This repo contains works of CENG391 course,Introduction to Image Understanding, and my studies about computer vision area.
Both C++ and Python's OpenCv library is used during laboratory studies of this course.The content of homeworks listed below.
- OpenCV Installation and Setup
- Basic data types and UI with OpenCV
- Smoothing & Sharpening operations
- Image compositing with Laplace pyramids
- Harris corner detection
- Image stitching for panorama generation
- Measuring the keypoint recognition rate, FAST & BRIEF
- Homography estimation, DLT
- Homography estimation with RANSAC
- Manuel image correspondence
- Bilateral filter algorithm
- Bilinear interpolation
- Object detection with RANSAC
- Epipolar Line
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project_rollor_deformation_detection
- This project is about finding deformation on rollers during production process in a factory. Normally, there are four different text on a roller. However, there may be some missing text due to production errors so the aim of this project is to find rollers that has missing text on it.
Figure1: A Roller sample
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project_balata_deformation_detection
- This project is about finding deformation on rollers during production process in a factory. Normally, a product should has specific dimensions. However, dimensions of a product can change due to some production errors. This project aims to find products which don't have desired dimensions.
Figure2: A sample product
- This project is about finding deformation on rollers during production process in a factory. Normally, a product should has specific dimensions. However, dimensions of a product can change due to some production errors. This project aims to find products which don't have desired dimensions.
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project_ffmpegCapture
- This project implements capturing a camera stream using ffmpeg library of C++ language. OpenCv library has a videoCapture library for capturing videos. However, I tried to implement a C++ class to capture frames more efficiently.
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project_count_people
- This project aims to count number of people entered a shop during the day using camera stream.
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project_create_heatmap
- This project aims to create heatmap of customers in a market. It creates heatmap for every hour in a day so it can be used to determine the most crowded hours of a day and the most used places in a market.
Figure3: Heatmap of a market using fisheye camera
- This project aims to create heatmap of customers in a market. It creates heatmap for every hour in a day so it can be used to determine the most crowded hours of a day and the most used places in a market.
