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mser's Introduction

MSER

Javascript implementation of Maximally Stable Extremal Regions (MSER) algorithm

Install

$ bower install mser

Description

This implementation is intended for realtime MSER detection in the browser (on a canvas rendering context ImageData object). For algorithm parameters, please read this article. The extract method returns an array with detected regions.

Usage

var canvas = document.getElementById("canvas"),
	context = canvas.getContext("2d"),
	mser = new MSER({
		delta: 2,
		minArea: 0.001,
		maxArea: 0.5,
		maxVariation: 0.5,
		minDiversity: 0.33
	}),
	regions = mser.extract(context.getImageData(50, 50, 100, 100));

// ...

mser's People

Contributors

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Stargazers

Manu avatar brianhumphreys avatar Rostam Dinyarian avatar Georg Dr. Fischer avatar Eddie Hsu avatar bokuweb avatar avatar Chaturanga Namal avatar Angga Maulana avatar avatar Adrien Gibrat avatar

Watchers

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Forkers

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mser's Issues

MSER blobing

Hello Sylvain,
Fantastic work on this implementation of MSER. I though I was going to be lost while doing this in the browser but your code has helped a lot. I have ran the demo and noticed that the algorithm performs box segmentation pretty well. I was wondering if it could output a black and white thresholded version of the input image. Is there a setting in your algorithm that I am missing that will allow me to do this?

If this is not possible currently but you have any helpful information that will help me fork your repo to add this functionality, then any response is much appreciated. Thank you.

Potential bug with minDiversity

Recursive call at line 135
child.process(delta, minArea, maxArea, maxVariation);
should probably pass minDiversity as 5th parameter

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