Logo Questions Linux Laravel Mysql Ubuntu Git Menu
 

How to detect Hotspots in an image

How to detect a hotspot in an image using opencv? I have tried googling but couldnt get a clue of it.

Description: I need to filter good images from a live video stream. In this case I need to just detect the Hotspot in a frame. I need to do this in opencv.

What is HotSpot?

Hot spots are shiny areas on a subject’s face which are caused by a flash reflecting off a shiny surface or by uneven lighting. It tends to make the subject look as if they are sweating, which is not a good look.

Update : http://answers.opencv.org/question/7223/hotspots-in-an-image/ http://en.wikipedia.org/wiki/Specular_highlight

The above two links also could help for my Post?

Image with HotSpot:

enter image description here

Image Without HotSpot:

enter image description here

like image 301
2vision2 Avatar asked Feb 11 '13 09:02

2vision2


People also ask

How do you identify a hot spot?

Analysts use geographic information systems (GIS) to combine street maps, data about crime and public disorder, and data about other features such as schools, liquor stores, warehouses and bus stops. The resulting multidimensional maps produce a visual display of the hot spots.

What are hotspots on an image?

Hotspots are points or areas on the image that pop up as a small window containing text when hovered over. Easygenerator helps you bring a common static image to life by making it clickable. Hotspots explain complex ideas combined on a single image in a much more effective way than a typical text block.


1 Answers

An automatic rough indication of these "hotspot" areas can be obtained by a gaussian filtering followed by a binarization. The expectation is that the "hotspot" is much brighter than the area around it, so after a gaussian filtering they will be at least slightly highlighted and, at the same time, image artifacts are reduced due to the nature of the low-pass filtering.

Example results follow. Binarization at 0.75 (range is always [0, 1]) after a simple conversion to grayscale, Binarization at 0.85 after a gaussian filtering in the B channel of the HSB colorspace:

enter image description hereenter image description here

In both cases large components were removed due to the assumption that "hotspots" aren't too big.

like image 70
mmgp Avatar answered Oct 21 '22 12:10

mmgp