Using the median distance to compare object shapes in content-based image retrieval

Turning Angles (TAs) representation is considered one of the most interesti ng methods for representing object shapes in content-based image retrieval systems. Nevertheless, the distance commonly used to measure the similarity between shapes represented by TAs, the Euclidean one, is generally too sen sitive to small variations in shapes. In this paper we present a new distance between shapes represented by TA, n amely the Median distance, specially devised to minimize the effects of sma ll variations in shapes. Its analytical properties are discussed and experi mental results are provided and compared with those obtained by applying tr aditional techniques based on Euclidean distance. The Median distance has b een implemented in the Automatic Image Storage and Retrieval (AISR) system, which allows storage and content-based retrieval of 2D images.