A Bag of Words Based Approach for Classification of HEp-2 Cell Images

In this work we present an automatic HEp-2 cell image classification technique that exploits different spatial scaled image representation and sparse coding of SIFT and SURF features. The proposed method is applied on the ICIP2013 dataset in the I3A workshop, which is held in ICPR 2014 conference. Experiments are designed to capture the accuracies on training set with cross validation method. Additionally, the prior information on positive and intensity levels of cells are used to boost the overall performance. Finally, different number of iterations on learning the dictionary is studied to find the optimum one.