Correlation

Correlation using Gaussian Function.  Used to detect round objects.
Still work in progress.
SlowCorrelation

Correlation via 2D Gaussian function using brute force (i.e., many
loops).  Code is slow so better runtime code must be written.
Considering FFT for improvements.
CorrelationAndNormalization

Previous implementation of correlation (renamed to ImageFitting) was
incorrect use of correlation; however, it still produced some
meaningful results.  Correct implementation is DetectionGaussian.
Algorithm is still slow so it needs improvement.  I also added a
normalization formula.
Correlation

Correlation with the Gaussian using mat lab’s built in cross
correlation; this leads to a much faster run time.  Correlation with
the Gaussian is detecting a lot of “noise” (i.e., non-circular
objects).  Thus, a new function, GeneralGaussian, allows normalized
cross correlation with any given image and a desired template (i.e.,
cropped part of image).  This is still producing “noise”, but still
generally improved results.  I must still figure out how to reduce this
“noise” and a good way to automatically detect cutoff value for
correlation.
Gabor Filter

Gabor filters to apply to slides. Hopefully helping with object
detection.
Merge pull request #5 from openconnectome/Correlation

Correlation