Research On Footprint Image Processing

Footprints are very important evidences that are easily found in the criminal case and very useful in serial and parallel processing of cases. But because of the limited techniques of footprint collection in crime scenes, the quality of the footprint is very low. And because every local police footprint management procedure is different from each other and the method is simple, it makes footprints can't be used as effectively as fingerprints in criminal case investigation.In this paper, the research on the footprint images is based on the knowledge of image processing. In order to improve the visual perception of the footprint images, the algorithms of image enhancement are applied. And in order to help the sole texture automatic identification and classification of the footprint images, the algorithms of image segmentation are used.To improve the quality of footprint images the unsharp masking method is proposed, which is based on multi-level hierarchical wavelet and direction information measure. In order to measure the quality of image enhancement algorithms, information capacity is used. Experimental results demonstrate that the algorithms enhanced footprint image detail and the signal to noise.To get the sole texture of footprints, the algorithms of fuzzy C-means clustering and Otsu algorithm are used. In this paper, an improved Otsu algorithm is proposed, which is based on the two-dimensional bound histogram. Experimental results demonstrate that these algorithms have good segmentation effect.