Welcome to AURlabCVsimulator

This repository is made for testing different computer vision methods by simulating a mission done in Trondheimsfjorden in April 2016

Libarys used

  • Python: 2.7.11 —Anaconda 2.5.0 (64-bit)

  • scipy: 0.17.0

  • numpy: 1.10.4

  • matplotlib: 1.5.1

  • pandas: 0.17.1

  • sklearn: 0.17

Folders of images to run simulations on

  • images_L&R_avoided obstacle first try
  • repeatExperiment
  • images close to transponder

Mehtods in AURlabCVsimulator

Stereo camera method: - Dipsarity method

Mono camera methods also called the texture based methods:

  • LBP ROI method
  • Haralick ROI method

  • SLIC Superpixel Locally Binary Pattern method

  • SLIC Superpixel Harlick method

Bellow are some examples:

Typical underwater image with an obstacle

Image with an obstacle

imageTest

EXAMPLE OF THE LBP ROI method

Predicted image with lbp

image_prediction_lbp

Display maskedImage image

maskedImage

Display countour center and boundingbox of the predicted obstacle

drawnImage_boundingBox_maskedImage.png

EXAMPLE OF THE PREDICTION WITH Haralick ROI method

image_prediction_lbp

EXAMPLE OF THE PREDICTION WITH SLIC Superpixel Locally Binary Pattern method

LBP_prediction_dots.png

Stereo camera methods

EXAMPLE OF THE Obstacle avoidance with Dipsarity method

disparityImageClean

Unifrom Local Binary Pattern (watch this to understand better): - https://www.youtube.com/watch?annotation_id=annotation_98709127&feature=iv&src_vid=wpAwdsubl1w&v=v-gkPTvdgYo

  • Lars Brusletto Master thesis