Auto-clustering of mugshots using multilayer Kohonen network

摘要

This paper proposes a multi-layer neural network system to classify police mugshots according to the contours of the heads. In order to efficiently acquire enough information from the mugshots, an interactive algorithm performing image pre-processing including segmentation and curve fitting is presented, by which the contours of the human heads are extracted. From the contours obtained, a set of feature vectors consisting of 16 normalized measures is gathered. Since the feature vectors are distributed non-linearly separable in Hilbert space, a two layer Kohonen network is implemented to cluster these vectors. It has been demonstrated and proved that the multi-layer Kohonen network has a performance of non-linear partition, so it has more powerful pattern separability than conventional Kohonen network. Meanwhile, the fact that two layer Kohonen network is enough for dealing with the current non-linear partition problem is expressed. About 100 samples of mugshots are involved in the research, and the results are given.