balloon61 / Perception-Project

Assignments in Computer Vision course. This repository including AR marker detect, Histogram equalization, Line detection, Stereo Vision, Turning prediction

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Perception-Project

Description:

This repository includes several basic perception project

Requirement:

numpy, cv2, matplotlib

AR Tag Detection:

Description:

Detect AR tag in any direction.

Result:

AR_detect_AdobeExpress (1)

Video 1. AR Tag detection

Coin Seperation

Description:

Calculate how many coins in this image.

Result:

Image processing is shown as follows, and the number of coins will be published in your terminal when you executed the code. Q1imageScreenshot from 2022-10-26 13-23-55

Fig 1. (Left) Preprocessing image (Right) After processing image

Historgram Equalization

Description:

Given a sequence of image and do Historgram Equalization and Adaptive Historgram Equalization to each images.

Result:

0000000000 Fig 2. Original image output00 Fig 3. Historgram Equalization (top) original (mid) Historgram Equalization (bot) Adaptive Historgram Equalization

Line Detection

Description:

Detect Lane in the highway.

Lane_detection_AdobeExpress

Video 2. Line Detection

Steering Prediction

Description:

Calculate the curvature of the lane in the highway and predict the steering direction.

Results:

turning_prediction_AdobeExpress (1)

Video 3. Turning Prediction

Stereo Vision

Description:

implement the concept of Stereo Vision. given several different datasets, each of them contains 2 images of the same scenario but taken from two different camera angles. By comparing the information about a scene from 2 vantage points, we can obtain the 3D information by examining the relative positions of objects.

Pipeline for creating a Stereo Vision System:

  1. Calibration: Get the F (fundamental matrix), K (intrinsic matrix), and E (essential matrix)
  2. Rectification: Apply the perspective transformation to make sure that the epipolar lines are horizontal for both images
  3. Correspondence: Get the disparity image which is the image that given where each pixels gives the disparity of the 3D points.
  4. Compute Depth Image: Directly use the disparity matrix to calculate the depth image.

Results:

Rectification:

Screenshot from 2022-10-26 13-51-10 Fig 4. Corresponding Eplliplolar line

Screenshot from 2022-10-26 13-50-59

Fig 5. Rectified

Correspondence:

Screenshot from 2022-10-26 13-50-27

Fig 6. Disparity

Depth Image:

Screenshot from 2022-10-26 13-52-40

Fig 7. Depth image

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Assignments in Computer Vision course. This repository including AR marker detect, Histogram equalization, Line detection, Stereo Vision, Turning prediction


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