# Online Signature Verification Systems on a Low-Cost FPGA
## 1 Introduction  
A handwritten signature requires a conscious action by the user, and therefore, it is one of the most usual methods by which persons claim their identity verification and accept responsibility for a signed document. Nonetheless, handwritten signatures have certain disadvantages, which have hindered their widespread use as biometric verification. The main challenge is the large intra-class and small inter-class variability. Samples taken from the genuine user may have large variability in their shapes. In addition, trained forgery signatures carried out by impostors may look very similar to signatures from the genuine user. Online signatures provide advantages for automatic biometric verification due to the additional information obtained from the capturing device, an electronic pen on a touch screen. Capturing angle and pressure samples, along with the shape coordinates, provides additional information about signature dynamics that increases inter-class variability. Biometric systems are typically developed on general-purpose microprocessors due to the development comfortability provided by programming languages and compilers. Implementation issues, such as power consumption, data format, processing speed, or memory requirements, are not generally considered since they are assumed to run on high-performance computers. In contrast, portable systems are generally based on low-cost embedded microprocessors featured by memory and computing limitations. In such cases,algorithm optimizations, hardware accelerators or custom computers can be explored to provide an efficient implementation. Biometric algorithms are usually composed of a set of computing stages that are used not only in different biometric modalities but also in computer vision, cryptography, and other fields. The computational requirements at some stages may hinder their applicability for real-time systems on general-purpose microprocessors. In such cases, the acceleration of some calculations by using FPGAs is an interesting possibility. Most of the works related to accelerators on FPGAs focus on a particular computing stage, such as the simplified FFT (Fast Fourier Transform) presented in [1], SVM (Support Vector Machine) implementations in [2] or the three-dimensional DTW (Dynamic Time Warping) architecture shown in [3]. However, complete biometric systems accelerated on FPGAs are scarce due to the development effort that must be carried out for their implementation. The work presented in [4] describes a pyramid-pipeline architecture of a convolutional neural network on FPGA for speaker recognition, and a complete biometric speaker verification system was presented in [5]. Other examples are the hardware accelerator of cryptosystem for iris, presented in [6], and the iris identification system on FPGA based on hardware-software co-design [7]. Related work about online signature biometrics on FPGA is even more scarce. The FPGA role described in [8] is to act as a wireless slave, which is connected to a computer executing a very simple signature algorithm. The online signature verification system proposed in [9] is based on a hardware accelerator, which has been deprecated by the second system presented in this paper. The paper is organized into six sections. The next section of the paper briefly describes the online signature verification algorithm, which is implemented in the presented systems. Section 3 starts describing the adopted replacements of the IEEE 754 double-precision format in order to efficiently implement the algorithm on a low-cost FPGA family. The section continues with an architecture overview of the three implemented systems, their main advantages and drawbacks. Section 4 shows a detailed explanation about the DTW stage implemented on these systems, not only because it vastly dominates the total execution time of the signature verification but also because it is widely adopted in other biometric modalities, such as speaker [10], electrocardiogram [11], iris [12], and many others.