Visual cortex inspired features for object detection in X-ray images

Visual cortex inspired features mimic what we know of the brain's visual cortex, which is still the best existing object detection system regarding speed and accuracy. For this paper we benchmarked two prominent implementations of these features, Mutch and Lowe's SLF-HMAX and Pinto et al.'s V1-like, against the popular local invariant features SIFT and PHOW in combination with the bag of visual words approach. The benchmark task was the detection of illicit objects in X-ray images of luggage. X-ray inspection is one of the main means of preventing the transport of illicit objects into sensitive areas. The visual cortex inspired features performed superior to the conventional features, probably owing to the textureless nature of X-ray images and the encoding of geometric information.