Edge orientation histogram back projection

Question

I am working on an object detection module using opencv , and I am using the "Edge Orientation Histogram" as the object descriptor.

after generating the histogram, I back project it onto the original image (after calculating the orientations in it to).

is that correct , because the back project output is showing a lot of white areas that are not the object that needs tracking.

the procedure goes like the following:

1. generate EOH for the target object using Sobel operator and the phase function.
2. calculate image edge orientations (no histogram) to project the histogram onto it.
3. perform backprojection from the EOH onto the orientation image.

I need confirmation that my assumptions are correct.

and does it make any sense, if i backprojected the EOH onto the image itself (grayscaled) not the orientation one ?!

some images for more illustration:

• the target is to track the panadole box .. the scene looks like the following: (Left)

• the orientation image after thresholding is the following (for the target) (middle)

• and the back projected image is the following: (right)

http://postimg.org/image/nzx7noav5/

thanks guys.

Answer 1

Well the back projection calculates the probability of a pixel whether it belongs to statistical model or not, look here OpenCV Back Projection. The reason you are encountering "White Areas" outside the target object can be because your object model is very generic. Can you provide some resultant images to further clarify your problem.