# Why should we normalize Bag of Features histograms?

each image is represented by a vector, typically 1000-4000 dimension, normalization with L1/L2 norm

Why we should normalize the feature histogram vector for image-classification/retrieval applications?

In addition, the distance used for normalize histograms should be the same for computing the distance between them? Because the standard distance used for BoF histograms is $\chi2$ distance, not L1/L2.