Update on the class to reflect the review. Split the class into virtual and implementation. change of name to LineSegmentDetector, using Input/Output-Arrays, general clean ups.

Example: img of size 10x10 and templ of size 11x9.
In subsequent code this will results in either width or height of
corrSize to be zero (0).
Line 261 will call crossCorr which will then have a zero size of either
blocksize.width or blocksize.height resulting in a division by zero
crach in lines 137 or 138.

http://www.code.opencv.org/issues/2023

eg:

In [3]: box = ((10,10),(5,5),0)

In [4]: cv2.boxPoints(box)
Out[4]:
array([[  7.5,  12.5],
       [  7.5,   7.5],
       [ 12.5,   7.5],
       [ 12.5,  12.5]], dtype=float32)

Yes, it's as ludicrous as it sounds, but it's still true. Bizarrely,
the previous commit makes CLAHE run about 10% slower on Android, even
though it doesn't even touch any CLAHE code. Splitting it off fixes that,
although the reason it does is a mystery for the ages.

It's cleaner when it's in its own file, anyway. ;=]

This should allow many algorithms to take advantage of more parallelization
technologies.

Ensure that all channels are considered when comparing multi-channel histograms

When comparing histograms that look like multi-channel images (e.g a 3D histogram, of 4x4x4 bins, might appear as a CV_32FC4 matrix), cv::compareHist would complain because it was expecting the matrix type() == CV_32F. Now we test matrix depth() == CV_32F instead.

The orientation of convexHull's result is currently the opposite of what the
documentation would suggest:

>>> import cv2, numpy as np
>>> points = np.array([[0,0],[0,1],[1,0]], dtype=np.int32)
>>> cv2.convexHull(points, clockwise=False)
array([[[1, 0]],
       [[0, 1]],
       [[0, 0]]], dtype=int32)
>>> cv2.convexHull(points, clockwise=True)
array([[[0, 0]],
       [[0, 1]],
       [[1, 0]]], dtype=int32)

Changing the function itself is probably not a good idea at this point, so
this fixes the documentation by flipping the coordinate system.

I also removed the mention of the origin, since it's irrelevant for this
function.

Clarified what value floodfill sets pixels in the mask to when FOODFILL_MASK_ONLY is set.

Also cv::, cv::gpu:: and cv::ocl:: namespace prefixes can be safely omitted
inside CV_ENUM and CV_FLAGS