Research On Segmentation Algorithm Of Multi-Fingers' Fingerprint

With the increasing requirements for security, biometrics based personal identification methods have been received extensive attention. Recently, Fingerprint recognition technology is becoming an active topic in biometrics due to its high reliability for personal identification, which can overcome the drawbacks of the traditional identification and widely used in the customs, airports, and other special high-security channel region. Accordingly, Fingerprint recognition technology has the important value of the study and application, and is an active topic in biometrics recognition.How to effectively improve the accuracy of fingerprint recognition is the core of fingerprint recognition. Multi-biometric fusion identification can effectively improve the accuracy of a single model biometric recognition, and multi-fingerprint recognition can improve the accuracy of a single fingerprint recognition, which wills not additional acquisition cost and software complexity of treatment, so this will become an important application in future. As the multi-fingerprint segmentation method is the foundation of multi-fingerprint recognition technology, according to the characteristics of fingerprint images and fingerprint acquisition hardware, the multi-fingerprint segmentation method would be studied by actual works required, and a new multi-finger fingerprint segmentation algorithm based on direction projection is provided.The fingerprint physiological characteristics, fingerprint acquisition hardware system, acquisition requirements, and characteristics of fingerprint images, which are foundation of fingerprint segmentation and provide the priori knowledge to design the segmentation algorithm, are introduced in the paper. Based on the above characteristics, the design, including image correction, image filtering processing, edge detection, the direction of projection, the main direction of acquisition and vertical projection, to determine the type of fingerprint segmentation and image quality evaluation part of the multi-finger fingerprint technology route, which includes pre-processing stage image correction, image filtering processing, edge detection process, are separated with the basic premise; separated stages, including the direction of projection, the main direction of acquisition and vertical projection, fingerprint segmentation process and the type of judge, etc., are the core of the algorithm, the fingerprint image quality evaluation After the partition of the fingerprint on a qualitative assessment, in order to enhance image recognition accuracy of the latter to lay the foundation. The above treatment refers to the process for multi-fingerprint segmentation provides an important technical support.Preprocess of multi-finger fingerprint fingerprints are many segmentation refers to the premise and foundation, and its concrete realization methods include bilinear interpolation algorithm, median filtering treatment, canny edge detection processes, bilinear interpolation algorithm will be collected in 2940×1840 of the original image data standardization for the 1812 * 1476 new images, reduces the effects of light aberration; median filter processing algorithms to reduce image noise and other interference; Canny edge detection to obtain fingerprint refers to the brink of many features, provide the basis for the direction of projection reduces the image acquisition process, the background light is different from the pressure difference, such as finger implications. Therefore, some pretreatment reduces image distortion, collecting environmental pollution to varying degrees, the background illumination of different areas such as the impact of many means for follow-up fingerprint image segmentation has laid a foundation.Multi-fingerprint segmentation algorithms are the core of this article and provide a basis for later identification. Multi-fingerprint segmentation process includes X direction's projection, Y direction's projection, threshold of X direction's projection, threshold of Y direction's projection, the main direction acquisition, each finger perpendicular to the main direction of projection and threshold, multi-fingerprint image segmentation type and fingerprint identification process. X direction of projection statistics of its vertical edge points of the number of fingerprints to obtain horizontal direction refers to many fingerprint projection distribution; Otsu threshold segmentation algorithm is used by X direction of projection threshold, the realization of the adaptive threshold selection, access to the horizontal direction refers to many fingerprints on the distribution of projection area, then use the projector with the merger of the region bound algorithm to obtain the horizontal direction on many of the projection distribution refers to the number of fingerprints and fingerprint of each of the space coordinates of the scope of the projector; Y direction of projection statistics of its horizontal direction the number of edge points fingerprint, access to many means a vertical projection of the distribution of fingerprints; Otsu threshold segmentation algorithm is used by Y direction projection threshold, the realization of the adaptive threshold selection, access to many means a vertical projection of the distribution of the fingerprint region , then the region ruled out the use of projection algorithm and combined to obtain the vertical projection of the many means the distribution of the number of fingerprints and fingerprint of each projection space coordinates of reference; X and Y direction in accordance with the distribution of projection, combined with many referring to the characteristics of fingerprint images, many means to obtain the main direction of the fingerprint image, and then statistics for each finger perpendicular to the main direction of the projection distribution, using Otsu threshold segmentation algorithm and projection region bound algorithm with the merger of its main direction of the vertical projection of the distribution of thresholds, access to each fingerprints fingers the scope of the space coordinates. According to the characteristics of multi-fingerprint images, each fingerprint image types are recognized automatically and automatic segmentation process of multi-fingerprints are completed.Fingerprint image quality evaluation of the partition after the treatment in the identification before the image quality for pre-evaluation to determine whether they meet the necessary requirements of image recognition, which can effectively improve the accuracy of fingerprint identification. In this paper, the fingerprint image of the fingerprint area and the overall mean gray level and gray-scale variance, block the gray mean and variance of gray-scale fingerprint image quality evaluation of key indicators, after the realization of fingerprint image segmentation quality evaluation, to judge whether meet the requirements, if it is necessary to meet the identification or not, they are required to re-acquisition.Using VC 6.0 developed many fingerprint segmentation refers to the experimental system, combined with the Matlab simulation analysis, collected for different circumstances, for many online and offline fingerprint segmentation test, experimental results show that this article refers to many fingerprint segmentation method are effective and can meet the needs of the actual partition identification. Therefore, this study refers to many fingerprints can be divided to provide a sense of reference.