Image-Processing-OpenCV | Image Processing using the OpenCV C API | Computer Vision library

by GeorgeSeif C++ Version: Current License: No License

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kandi X-RAY | Image-Processing-OpenCV Summary

Image-Processing-OpenCV is a C++ library typically used in Artificial Intelligence, Computer Vision, OpenCV applications. Image-Processing-OpenCV has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Image Processing using the OpenCV C++ API

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Image-Processing-OpenCV has a low active ecosystem.

It has 23 star(s) with 23 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

Image-Processing-OpenCV has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Image-Processing-OpenCV is current.

Quality

Image-Processing-OpenCV has no bugs reported.

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Image-Processing-OpenCV has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

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Image-Processing-OpenCV does not have a standard license declared.

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Community Discussions

Trending Discussions on Image-Processing-OpenCV

OpenCV - Estimating Box dimensions in Python

QUESTION

OpenCV - Estimating Box dimensions in Python

Asked 2017-Jan-24 at 10:08

This is the continuation of my previous question. I now have an image like this

Here the corners are detected. Now I am trying to estimate the dimensions of the bigger box while smaller black box dimensions are known.

Can anyone guide me what is the best way to estimate the dimensions of the box? I can do it with simple Euclidean distance but I don't know if it is the correct way or not. Or even if it is the correct way then from a list of tuples (coordinates) how can I find distances like A-B or A-D or G-H but not like A-C or A-F?

The sequence has to be preserved in order to get correct dimensions. Also I have two boxes here so when I create list of corners coordinates then it should contain all coordinates from A-J and I don't know which coordinates belong to which box. So how can I preserve that for two different boxes because I want to run this code for more similar images.

Note: The corners in this image is not a single point but a set of points so I clustered the set of the corner and average them to get a single (x,y) coordinate for each corner.

I have tried my best to explain my questions. Will be extremely glad to have some answers :) Thanks.

...

ANSWER

Answered 2017-Jan-24 at 08:26

In general you cannot, since any reconstruction is only up to scale.

Basically, given a calibrated camera and 6 2D-points (6x2=12) you want to find 6 3D points + scale = 6x3+1=19. There aren't enough equations.

In order to do so, you will have to make some assumptions and insert them into the equations.

Form example:

The box edges are perpendicular to each other (which means that every 2 neighboring points share at least one coordinate value).
You need to assume that you know the height of the bottom points, i.e. they are on the same plane as your calibration box (this will give you the Z of the visible bottom points).

Hopefully, these constraints are enough to given you less equations that unknown and you can solve the linear equation set.

Source https://stackoverflow.com/questions/41821446

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