Using Correlation Method For Match Two Digital Images

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We have used correlation method to match two digital images. This technique is also known as template matching. It compares portions of one image against another on a pixel-by-pixel basis.
Correlation is a measure of degree to which two variables agree, not necessarily in actual value but in general behavior .The two variables are the corresponding pixel values in two images , template and source.

The matching process moves the template image to all possible positions in a larger source image and computes a numerical index that indicates how well the template matches the image in that position.
Template is nothing but a small region of image. Correlation method is simple and hence can be analyzed appreciatively. There are two key features which make it simple and they are: shift-invariant and linear.Shift-invariant means that we perform the same operation at every point in the image. Linear means replacing every pixel with a linear combination of its neighbours.
The goal of this method is to find the correlated pixel within a certain disparity range that minimizes the associated error and maximizes the similarity.

The authenticated result is the presented in this section.
Data set of Test Ear localization Accuracy(%)
Images Reported in Proposed Method

Data Set 1 801 95.88 99.25
Data Set 2 802 94.73 98.50
Data Set 3 1070 91.11 95.61

1. The proposed technique breaks the derived edges of the profile face into a set of convex
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