OpenCV image comparison in Android

You should understand that this is not a simple question and you have different concepts you could follow. I will only point out two solution without source-code.

1. Histogram comparison: You could convert both images into grey-scale make a histogram in the range of [0,…,255]. Every pixel-value will be counted. Then use both histograms for comparison. If the distribution of pixel-intensities equals or is above some treshold (perhaps 90% of all pixels), you could consider this images as duplicates. BUT: This is one of the simplest solutions and it isn’t stable if any picture has an equal distribution.
2. Interest-Point-Detectors/-Descriptors: Take a look at SIFT/SURF image-detectors and descriptors. A detector will try to determine unique keypoits of intensities in an image. A descriptor will be computed at this location I(x,y). A normal matcher with a bruteforce-approach and euclidean distance can match these images using their descriptors. If an image is a duplicate the rate of given matches should very high. This solution is good to implement and there could be enough tutorials regarding this topic.

I’ll hope this helps. Please ask if you have questions.

[UPDATE-1]
A C++-tutorial: http://morf.lv/modules.php?name=tutorials&lasit=2#.UR-ewKU3vCk

Some JavaCV-tutorials: http://code.google.com/p/javacv/w/list

[UPDATE-2]
Here is an example with SIFT-Detector and SIFT-Descriptor using default parameters. RANSAC-Threshold for homography is 65, reprojection-error (epsilon) is 10, cross-validation enabled. You could try to count the matched. If the Inliner-Outlier-Ratio is too high you could see this pair as duplicates.

For example: These images produce 180 keypoints in IMG1 and 198 in IMG2. The matched descriptors are 163 of which only 3 are outliers. So this gives a really good ratio which only could mean that these images could be duplicates.

[UPDATE-3]
I don’t understand why you can initialize the MatOfKeypoints. I’ve read the API and there’s a public constructor. AND: You can use the Mat of the image you want to analyse. This is very nice. =)

MatOfKeyPoint reference = new MatOfKeyPoint(matOfReferenceImage);

For Matching use a BRUTEFORCE_SL2 Descriptor-Matcher cause you will need the euclidean distance for SURF or SIFT.