Mohamed Benkedadra

Mohamed Benkedadra
Université de Mons · Department of Computer Science

About

1
Publication
2,432
Reads
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0
Citations
Citations since 2017
1 Research Item
0 Citations
20172018201920202021202220230.00.20.40.60.81.0
20172018201920202021202220230.00.20.40.60.81.0
20172018201920202021202220230.00.20.40.60.81.0
20172018201920202021202220230.00.20.40.60.81.0
Introduction
Education
September 2015 - September 2020
Université Abdelhamid Ibn Badis Mostaganem
Field of study
  • Computer Science

Publications

Publication (1)
Article
There are several studies on road lane detection but very few address adverse conditions for acquisition such as sun glare. Loss of details in underexposed images captured facing a low sun leads to misleading road lane detection. High Dynamic Range Imaging methods are used to acquire most details in such scenes. Unfortunately, these techniques are...

Questions

Question (1)
Question
Hello,
I have been writing code for a paper and I'm reading an image in RGB space in OpenCV which means that its read as a 3D matrix (HEIGHT x WIDTH x 3 (RGB) ).
I'm flattening the image into a 2D matrix ( NB_PIXELS x 3 (RGB) ) using this code :
image = image.reshape(len(image) * len(image[0]), len(image[0][0]))
This flattening process is an important step in the method that I'm going over in the paper.
Since I can't have the paper depend on a library like NumPy I would like a more elegant way to explain the flattening. Are there any papers that I can reference or any equations, methods ..etc that I can use as a replacement to the code that I shared?
Thank you!

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