1.1 Introduction
Signature is a special case of handwriting that can be considered as an image. There is a growing interest in the area of signature recognition and verification (SRVS) since it is one of the important ways to identify a person. Recognition is finding the identification of the signature owner. Signature has been a distinguishing feature for person identification through ages.
As a prelude to other parts of this study, this chapter will discuss the background upon which this study was initiated, the statement of problems that led to this study, the Aim and Objectives of the study. Others are Significance of the study, Scope of work, Limitations of the Study and Definition of technical terms.
1.2 Background of Study
Signatures for long have been used for automatic clearing of cheques in the banking industry. Despite an increasing number of electronic alternatives to paper cheques, fraud perpetrated at financial institutions in the United States has become a national epidemic. Since commercial banks pay little attention to verifying signatures on cheques mainly due to the number of cheques that are processed daily a system capable of screening casual forgeries will prove beneficial. Most forged cheques contain forgeries of this type. We in our project have tried developing a robust system that automatically authenticates documents based on the owner’s handwritten signature.
Authentication is the way towards proving, verifying and checking ones identity. It can be very well sorted or categorized in three types: something we know, similar to passwords; something we have, like a bus tickets or tokens; and, something we are, similar to our face, voice, signatures, etc. The third type is also known as Biometric. Together, these sorts are known as 3 factors of confirmation. Biometrics implies the programmed proof of an individual person based on his/her physiological or social attributes. This strategy of verification is preferred over conventional methods including and user’s passwords and PIN numbers for its exactness and case affectability. A biometric structure is fundamentally a model for example acknowledgment framework which makes an individual distinguishing proof by deciding the realness of a particular physiological or social trademark controlled by the client. These attributes are quantifiable and special Identification should be possible utilizing an individual’s character dependent on biometric estimations.
Approaches to signature verification fall into two categories according to the acquisition of the data: On-line and Off-line. On-line data records the motion of the stylus while the signature is produced, and includes location, and possibly velocity, acceleration and pen pressure, as functions of time. Online systems use this information captured during acquisition. These dynamic characteristics are specific to each individual and sufficiently stable as well as repetitive. Off-line data is a 2-D image of the signature. Processing Off-line is complex due to the absence of stable dynamic characteristics. Difficulty also lies in the fact that it is hard to segment signature strokes due to highly stylish and unconventional writing styles. The non-repetitive nature of variation of the signatures, because of age, illness, geographic location and perhaps to some extent the emotional state of the person, accentuates the problem. All these coupled together cause large intra-personal variation.
A robust system has to be designed which should not only be able to consider these factors but also detect various types of forgeries. The system should neither be too sensitive nor too coarse. It should have an acceptable trade-off between a low False Acceptance Rate (FAR) and a low False Rejection Rate (FRR). The false rejection rate (FRR) and the false acceptance rate (FAR) are used as quality performance measures. The FRR is the ratio of the number of genuine test signatures rejected to the total number of genuine test signatures submitted. The FAR is the ratio of the number of forgeries accepted to the total number of forgeries submitted. When the decision threshold is altered so as to decrease the FRR, the FAR will invariably increase, and vice versa.
1.3 Statement of Problems
Investigation reveals the problems of the Signature Recognition and Verification System which entails that:
- Information required for identification is not sensitive.
- Forging of one’s signature does not mean a long-life loss of that one’s personality.
- Recognizing signatures ignoring the variations such as: variations due to different pens, variations arising out of the fact that “No two signatures of the same person are exactly same”, and any marks on the paper or any such element.
1.4 Aim and Objectives of Study
The aim of the study is to design and implement a Signature Recognition and Verification System using Lapo Microfinance Bank as a case study. In achieving this aim, the following specific objectives were laid out as follows to develop an application software that will:
- Identify the signature owner,
- Make decision whether the signature is genuine or forger.
- Ensure fraud detection regardless of the account individual signatory.
1.5 Significance of Study
The relevance of the study is for identification of a particular human being signatures prove to be an important biometric. The signature of a person is an important biometric attribute of a human being which can be used to authenticate human identity. However human signatures can be handled as an image and recognized using computer vision. With modern computers, there is need to develop fast algorithms for signature recognition. There are various approaches to signature recognition with a lot of scope of research.
This study will be of immense benefit to other researchers who intend to know more on this study and can also be used by non-researchers to build more on their research work. This study contributes to knowledge and could serve as a guide for other study.
1.6 Scope of Study
The study focuses on the Design and Implementation of a Signature Recognition and Verification System which is not expensive to develop, reliable regardless of the individual, whether under different emotions, user friendly in terms of configuration, and robust against frauds. The study is limited to Lapo Microfinance Bank in Nigeria.
1.7 Limitations of the Study
During the course of this study, many things militated against its completion, some of which are:
- Time Constraint: The time frame given to accomplish this project was very short due to school academic calendar and it was carried out under pressure which made the researcher not to implement some necessary features.
- Research material: availability of research material is a major setback to the scope of the study.
- Frequent power failure: This made the researcher append more money on fuel to ensure sustainable power.
- Financial Constraint: Insufficient fund tends to impede the efficiency of the researcher in sourcing for the relevant materials, literature or information and in the process of data collection (internet).
1.8 Definition of Terms
Financial Institution: Financial institution is a company engaged in the business of dealing with financial and monetary transactions such as deposits, loans, investments, and currency exchange.
Signature: It is a handwritten (and often stylized) depiction of someone’s name, nickname, or even a simple “X” or other mark that a person writes on documents as a proof of identity and intent.
Identification: The action or process of identifying someone or something or the fact of being identified.
Authentication: The process or action of proving or showing something to be true, genuine, or valid.
Forgery: The action of forging a copy or imitation of a document, signature, banknote, or work of art.
Identity: Identity is the qualities, beliefs, personality, looks and/or expressions that make a person.
Hardware: Hardware is a physical part of a computer that can be touched, seen, feel which are been control by the software to perform a given task.
Database: Database is the collection of related data in an organized form.
Programming: Programming is a set of coded instruction which the computers understands and obey.
Technology: Technology is the branch of knowledge that deals with the creation and use technical and their interrelation with life, society and the environment, drawing upon such as industrial art, engineering, applied science and pure science.
Algorithm: A set of logic rules determined during the design phase of a data matching application. The ‘blueprint’ used to turn logic rules into computer instructions that detail what step to perform in what order.
Application: The final combination of software and hardware which performs the data matching.
Data matching database: A structured collection of records or data that is stored in a computer system.
Data integrity: The quality of correctness, completeness and complain with the intention of the creators of the data i.e ‘fit for purpose’
Password: This is a secret code that a user must type into a computer to enable he/she access it or its applications. This is made up of numbers, letters, characters or contribution of any of the above categories.
PHP: Hypertext Preprocessor (the name is a recursive acronym) This is a Programming language known as a server-side scripting language. It was used in the developing of this software.
Identification: The act of recognizing and naming someone or something.
Verification: Evidence that establishes or confirms the accuracy or truth of something.
Query language: A database query language and report writer allows users to interactively interrogate the database, analyze its data and update it according to the user’s privileges on data. It also controls the security of the database.
