**3.2. Iris**

Iris recognition is one of the most reliable methods for personal identification. The use of iris texture analysis for biometric identification is clearly well established with the advantages of uniqueness and stability. Iris recognition has been successfully applied in access control systems managing large databases. The United Arab Emirates has been using iris biometrics for border control and expellees tracking purposes for the past decade [3].

Iris is one of the most valuable traits for automatic identification of human being. A number of reasons justify this interest. First of all, the iris is a protected internal organ of the eye that is visible from the exterior. The iris is an annular structure and planar shape that turns easily, and it has a rich texture. Furthermore, iris texture is predominantly a phenotypic with limited genetic penetrance. The appearance is stable over lifetime, which holds tremendous promise

**Figure 1.** Block diagram of a face recognition system.

**Figure 2.** An original and a preprocessed face image.

for leveraging iris recognition in diverse application scenarios such as border control, forensic investigations, and cryptosystems.

There are also some drawbacks with it. It needs much user cooperation for data acquisition, and it is often sensitive to occlusion. Iris data acquisition needs a controlled environment. Additionally, data acquisition devices are quite costly. Iris recognition cannot be used in a covert situation.

Due to its low cost, user friendly system, high speed, and high accuracy of palmprint recognition, it can be considered as one of the most reliable and suitable biometric recognition system. A lot of work has already been done about palmprint recognition, since it is a very interesting research area. However, more research is needed to obtain efficient palmprint sys-

Person Identification Using Multimodal Biometrics under Different Challenges

http://dx.doi.org/10.5772/intechopen.71667

85

There are three groups of marks which are used in palmprint identification [5] as geometric features, line features (e.g., principle lines, wrinkles), and point features (e.g., minutiae points). A typical palmprint recognition system consists of palmprint acquisition, preprocess-

tem [4].

ing, feature extraction, and matching phases [6].

**Figure 3.** Block diagram of an iris recognition system [1].

**Figure 4.** Palmprint features (a) a high-resolution image and (b) a low-resolution image.

A typical iris recognition system has four different modules such as acquisition, segmentation, normalization, and matching. These modules are shown in **Figure 3** for a general iris recognition system.

### **3.3. Palmprint**

The palmprint recognition system is considered as one of the most successful biometric systems that are reliable and effective. This system identifies the person based on the principal lines, wrinkles, and ridges on the surface of the palm. Studies and research over 10 years have proven that the interesting feature of palmprint is fixed and invariant, and a palmprint acquired from any person is unique, so it can be reliable as a biometric trait.

Some of the advantages of the palmprint recognition compared with other biometric trait systems are invariant line structure, low intrusiveness, and the low cost of capturing device. Palmprint identification requires either high (refers to 400 dpi or more) or low (refers to 150 dpi or less) resolution images in which high-resolution images are suitable for forensic applications such as criminal detection [4] and low-resolution images are more suitable for civil and commercial applications such as access control. High-resolution and low-resolution palmprint images are demonstrated in **Figure 4**. Additionally, the area of palmprint is larger than fingerprint; consequently, there is a possibility of capturing more distinctive features in it.

Person Identification Using Multimodal Biometrics under Different Challenges http://dx.doi.org/10.5772/intechopen.71667 85

**Figure 3.** Block diagram of an iris recognition system [1].

for leveraging iris recognition in diverse application scenarios such as border control, forensic

There are also some drawbacks with it. It needs much user cooperation for data acquisition, and it is often sensitive to occlusion. Iris data acquisition needs a controlled environment. Additionally, data acquisition devices are quite costly. Iris recognition cannot be used in a

A typical iris recognition system has four different modules such as acquisition, segmentation, normalization, and matching. These modules are shown in **Figure 3** for a general iris

The palmprint recognition system is considered as one of the most successful biometric systems that are reliable and effective. This system identifies the person based on the principal lines, wrinkles, and ridges on the surface of the palm. Studies and research over 10 years have proven that the interesting feature of palmprint is fixed and invariant, and a palmprint

Some of the advantages of the palmprint recognition compared with other biometric trait systems are invariant line structure, low intrusiveness, and the low cost of capturing device. Palmprint identification requires either high (refers to 400 dpi or more) or low (refers to 150 dpi or less) resolution images in which high-resolution images are suitable for forensic applications such as criminal detection [4] and low-resolution images are more suitable for civil and commercial applications such as access control. High-resolution and low-resolution palmprint images are demonstrated in **Figure 4**. Additionally, the area of palmprint is larger than fingerprint; consequently, there is a possibility of capturing more distinctive

acquired from any person is unique, so it can be reliable as a biometric trait.

investigations, and cryptosystems.

**Figure 2.** An original and a preprocessed face image.

84 Human-Robot Interaction - Theory and Application

covert situation.

recognition system.

**3.3. Palmprint**

features in it.

Due to its low cost, user friendly system, high speed, and high accuracy of palmprint recognition, it can be considered as one of the most reliable and suitable biometric recognition system. A lot of work has already been done about palmprint recognition, since it is a very interesting research area. However, more research is needed to obtain efficient palmprint system [4].

There are three groups of marks which are used in palmprint identification [5] as geometric features, line features (e.g., principle lines, wrinkles), and point features (e.g., minutiae points). A typical palmprint recognition system consists of palmprint acquisition, preprocessing, feature extraction, and matching phases [6].

**Figure 4.** Palmprint features (a) a high-resolution image and (b) a low-resolution image.
