Recognizing Blasting Caps in X - Ray Images

This paper presents work in progress on an approach to the problem of recognizing blasting caps in x-ray images. An analysis of functional properties of blasting caps was used to design the representation space, which combines intensity and shape features. Recognition proceeds in two phases. The rst phase is a bottom-up process in which low intensity blobs are used as attention-catching devices to generate object hypotheses. The second phase is a top-down process in which object hypotheses are connrmed or rejected by t-ting a local model to ribbons surrounding the low intensity blob. The local model is acquired using inductive learning. Flexible matching routines are used during recognition that provide a measure of conndence for the identiication. Experimental results demonstrate the ability to learn the relationship between image characteristics and object functionality.