The study of Park [15] showed the experimental results of selleck bio applying SIFT [10,11] to fingerprint verification. However, http://www.selleckchem.com/products/MDV3100.html his work has some disadvantages which lead to poor performance in terms of both accuracy and speed. Firstly, fingerprint images were insufficiently preprocessed in the image. The histogram equalization which was applied in [15] was inadequate because it can lead to different brightness in different regions of fingerprint images. Secondly, the original SIFT matcher is unsuitable for fingerprint verification because a fingerprint primarily comprises parallel ridges or valleys, thereby making the Inhibitors,Modulators,Libraries features less distinctive. Thirdly, the low computational efficiency is a hindrance to practical applications.
The proposed technique uses key points of SIFT for fingerprint verification.
The proposed Inhibitors,Modulators,Libraries algorithm has several advantages over previous SIFT-based methods. Firstly, the proposed approach utilizes proper image processing to make the SIFT feature extraction robust against variations attributable to different finger pressures and noises. Inhibitors,Modulators,Libraries Secondly, the SIFT matcher is optimized for fingerprint verification based on a Hough Transform to expand the fingerprint images into large rotation cases. Thirdly, in order to enable the recognition system to perform in real time, a two-step fast matcher is proposed.The rest of this paper is organized as follows: Section 2 presents definition of SIFT-based minutia descriptor (SMD). Section 3 describes the procedures for the two-step fast matcher, called improved All Descriptor-Pair Matching (iADM).
Section 4 presents the experimental results and analysis to confirm the validity of the proposed method, named Fingerprint Inhibitors,Modulators,Libraries Identification using SMD and Inhibitors,Modulators,Libraries iADM (FISiA). Section 5 gives a brief conclusion.2.?SIFT-Based Minutia Descriptor (SMD)In this section, we present Inhibitors,Modulators,Libraries the flow of Inhibitors,Modulators,Libraries image processing, minutiae extraction and the definition of SIFT-based Minutia Descriptor.2.1. Fingerprint Image PreprocessingThe SIFT descriptor becomes unstable in the presence of variations in finger pressure or differences in skin characteristics. Therefore, the gray-scale fingerprint images without pre-processing are not proper for original SIFT extraction.
Filters are used to process the original fingerprint image to derive an enhanced gray image. Figure 3 shows Inhibitors,Modulators,Libraries the image processing flow employed in GSK-3 FISiA.
It can be partitioned into the following major stages: highpass filter, lowpass filter, ridge direction Drug_discovery detection, and ridge enhancement.Figure 3.Image processing flow.The highpass filter is used to perform the brightness calibration. If the gray value of the image at position (x,y) is denoted by I(x,y), the calculation of highpass filter IH(x,y) is Belinostat chemical structure computed in Equation Y-27632 2HCL (1) where the size of highpass window k is selected as 16 and the bias value b equals 128. It calculates average intensity within k �� k window and subtracts average from the center pixel biased at b.