Content Based Retrieval of Malarial Positive Images

The basic unit of a CBIR system is a bundle of pixels which have some meaning in the semantics of human life, further more the number of objects in an image, the greater is the need for annotation. The interpretation of the objects depicted in an image depends upon the perception and possible mathematical measurements like size/shape of parasites which can be calculated, so that it may be helpful in the diagnosis of malaria and it becomes an aid to doctors. So developing an annotation based upon a particular hypothesis may lead to a reduction in the semantic gap as it may require exact information like which parasite. The overall performance of CBIR system and the validation of true value facts, distributions based on which the annotation scheme is being developed for particular goal of CBIR becomes questionable. Thus, in this research work we have done the ground truth. Using new site features with multiple model framework is performing well in terms of recall and precision.