The Technologies Of Enhancement And Feature Extraction For Low-quality Fingerprint Image

So far, the existent fingerprint recognition researches both at home and abroad are always concentrated to common applications, such as the gate controlling, the information security, remote confirmation, which demand for the clearness, integrity, and high contrast of fingerprint images. However, the criminal's fingerprints withdrew from the spot are not sufficient, and even worse, the contrast of the textures is also low. Therefore, it will be difficult to achieve desired results by using traditional techniques to process such poor quality fingerprint images.This paper is mainly researched on poor fingerprint images, and has made further researches on the key technologies of the fingerprint auto-recognition system, such as the segmentation, enhancement, and feature extraction techniques of these images.The main work and novelty of this paper is:(1) Since the traditional fingerprint's segmentation algorithm based on block and point, is prone to make error segmentation so as to get white-block effect and can't make effective segmentation between the effective area and background. Then this paper proposes a new segmentation algorithm for the low-quality fingerprint's efficient area, which combines edge extraction with morphologic filtering techniques. The algorithm uses Canny operator to get the edge, so as to achieve the coarse segmentation of the foreground model. Then a morphologic method is employed. An appropriate structural element is selected to correct the edge in the effective area and reduce noise. Then it will segment the background and foreground not only effectively but also exactly. By experiment with fingerprint, this algorithm can reduce the noise of the background, while avoiding the losing of ridge line's information in the effective areas.(2) Make researches on two traditional image enhancement techniques: directional filter and traditional Gabor filter. By experiment, it shows that traditional Gabor filter can achieve better enhancement effect than directional filter when processing low-quality fingerprint images. Since the traditional Gabor filter has such drawbacks as low preciseness of the direction parameters of the texture lines, and the low efficiency of the resolution of the frequency parameter, the blocked directional image is distinguished by using directional images with various scales to obtain more precise direction parameter. A novel method is employed to get the mean frequency of the ridge lines. Unlike the traditional Gabor filter using the texture line frequency parameter, mean frequency is used instead, and the efficiency of the resolving is improved greatly. Lastly, the filtering window of the traditional Gabor filter is improved. A new filtering window , which can adjust its size and direction adaptively according to the direction of local texture and frequency, is used in the enhancement of the fingerprint images. When enhancing images based on segmentation, it shows that the improved method has more privilege over former ones both on enhancement effect and time costing.(3) Binarize the enhanced fingerprint image using binary techniques based on local adaptive threshold. For the attended binary images, on one hand, if the threshold is large excessively, it will be prone to get sticks on the valley line; on the other hand, if the threshold is small excessively, it is prone to get bobs on the ridge line. Then a denoising algorithm is proposed, which eliminates the sticks according to the block direction, and fills the bobs according to the neighborhood. Utilize an improved fingerprint image thinning algorithm. After thinning, texture lines become smooth and clear, and at the same time hold the texture construction of the low-quality fingerprint images. For those thinned images, select the end minutiae and bifurcation as their true feature and extract such features, and then make a processing to eliminate the false minutiae and reserve the true minutiae. Experiment shows that the binary image after demoting process, are much clearer and the texture lines are much smoother.