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Re: [help-GIFT] Histograms and Normalization

From: David Squire
Subject: Re: [help-GIFT] Histograms and Normalization
Date: Wed, 04 Jun 2003 17:08:46 +1000
User-agent: Mozilla/5.0 (X11; U; Linux i686; en-US; rv:1.3) Gecko/20030312

Sailesh Suvarna wrote:
Hi all,
Thanks for the answers to my last question.

I have some more...........

I am using just 4 images in my collection and am using only feature (1) - 
Colour Histograms.

Thats's not one feature, that's one *feature group*.

In  CWeightingFunction::subApply if I change-


This is doing histogram intersection. In fact it is calculating the intersection for just one bin of the histogram, corresponding a particular feature.

to find out the difference rather than similarity

The system expects scores to be maximal for an image with identical features to the query. This version will be zero when the features are identical. This is likely to cause problems later...

I get the following results: Similarity: inf
Similarity: nan
Similarity: inf
Similarity: inf

Yep. Problems. If I remember correctly, the similarity scores are normalized by dividing by the similarity of the query with itself, which you have just set up to be zero. Hence problems caused by divide-by-zero errors.

NB. This interpretation is not based on detailed knowledge of this code. Wolfgang: jump all over me if I'm wrong!

Also the lQueryScore always computes to 0
The following is what I get Pruning used!
 Pruning: I will evaluate 39 Features.

Note: 39 features, not one.



Dr. David McG. Squire, Postgraduate Research Coordinator (Caulfield),
Computer Science and Software Engineering, Monash University, Australia
Monash Provider No. 00008C

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