You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Graphical passwords: a survey 
Chapter Title:  Recognition Based Techniques 
1. Abstract of Cited Paper (BIB001):  There is a trade-off between security and usability in user authentication for mobile phones. Since such devices have a poor input interfaces, 4-digit number passwords are widely used at present. Therefore, a more secure and user friendly authentication is needed. This paper proposes a novel authentication method called “Awase-E”. The system uses image passwords. It, moreover, integrates image registration and notification interfaces. Image registration enables users to use their favorite image instead of a text password. Notification gives users a trigger to take action against a threat when it happens. Awase-E is implemented so that it has a higher usability even when it is used through a mobile phone. 
2. Abstract of Cited Paper (BIB002):  We identify a wide range of human memory phenomena as potential certificates of identity. These "imprinting" behaviors are characterized by vast capacity for complex experiences, which can be recognized without apparent effort and yet cannot be transferred to others. They are suitable for use in near zero-knowledge protocols, which minimize the amount of secret information exposed to prying eyes while identifying an individual. We sketch several examples of such phenomena[1-3], and apply them in secure certification protocols. This provides a novel approach to human-computer interfaces, and raises new questions in several classic areas of psychology. 
3. Abstract of Cited Paper (BIB003):  Graphical password schemes have been proposed as an alternative to text passwords in applications that support graphics and mouse or stylus entry. In this paper we detail what is, to our knowledge, the largest published empirical evaluation of the effects of user choice on the security of graphical password schemes. We show that permitting user selection of passwords in two graphical password schemes, one based directly on an existing commercial product, can yield passwords with entropy far below the theoretical optimum and, in some cases, that are highly correlated with the race or gender of the user. For one scheme, this effect is so dramatic so as to render the scheme insecure. A conclusion of our work is that graphical password schemes of the type we study may generally require a different posture toward password selection than text passwords, where selection by the user remains the norm today.

Literature Review:
Dhamija and Perrig  proposed a graphical authentication scheme based on the Hash Visualization technique  . In their system, the user is asked to select a certain number of images from a set of random pictures generated by a program ( figure 1) . Later, the user will be required to identify the preselected images in order to be authenticated. The results showed that 90% of all participants succeeded in the authentication using this technique, while only 70% succeeded using text-based passwords and PINS. The average log-in time, however, is longer than the traditional approach. A weakness of this system is that the server needs to store the seeds of the portfolio images of each user in plain text. Also, the process of selecting a set of pictures from the picture database can be tedious and time consuming for the user. Akula and Devisetty's algorithm  is similar to the technique proposed by Dhamija and Perrig  . The difference is that by using hash function SHA-1, which produces a 20 byte output, the authentication is secure and require less memory. The authors suggested a possible future improvement by providing persistent storage and this could be deployed on the Internet, cell phones and PDA's. Weinshall and Kirkpatrick BIB003 sketched several authentication schemes, such as picture recognition, object recognition, and pseudo word recognition, and conducted a number of user studies. In the picture recognition study, a user is trained to recognize a large set of images (100 -200 images) selected from a database of 20,000 images. After one to three months, users in their study were able to recognize over 90% of the images in the training set. This study showed that pictures are the most effective among the three schemes tested. Pseudo codes can also be used, but require proper setting and training. Sobrado and Birget  developed a graphical password technique that deals with the shouldersurfing problem. In the first scheme, the system will display a number of pass-objects (pre-selected by user) among many other objects. To be authenticated, a user needs to recognize pass-objects and click inside the convex hull formed by all the pass-objects (figure 2). In order to make the password hard to guess, Sobrado and Birget suggested using 1000 objects, which makes the display very crowded and the objects almost indistinguishable, but using fewer objects may lead to a smaller password space, since the resulting convex hull can be large. In their second algorithm, a user moves a frame (and the objects within it) until the pass object on the frame lines up with the other two passobjects. The authors also suggest repeating the process a few more times to minimize the likelihood of logging in by randomly clicking or rotating. The main drawback of these algorithms is that the log in process can be slow. Man, et al.  proposed another shoulder-surfing resistant algorithm. In this algorithm, a user selects a number of pictures as pass-objects. Each pass-object has several variants and each variant is assigned a unique code. During authentication, the user is challenged with several scenes. Each scene contains several pass-objects (each in the form of a randomly chosen variant) and many decoy-objects. The user has to type in a string with the unique codes corresponding to the pass-object variants present in the scene as well as a code indicating the relative location of the passobjects in reference to a pair of eyes. The argument is that it is very hard to crack this kind of password even if the whole authentication process is recorded on video because where is no mouse click to give away the pass-object information. However, this method still requires users to memorize the alphanumeric code for each pass-object variant. Hong, et al.  later extended this approach to allow the user to assign their own codes to pass-object variants. Figure 3 shows the log-in screen of this graphical password scheme. However, this method still forces the user to memorize many text strings and therefore suffer from the many drawbacks of text-based passwords. "Passface" is a technique developed by Real User Corporation [15] . The basic idea is as follows. The user will be asked to choose four images of human faces from a face database as their future password. In the authentication stage, the user sees a grid of nine faces, consisting of one face previously chosen by the user and eight decoy faces (figure 4). The user recognizes and clicks anywhere on the known face. This procedure is repeated for several rounds. The user is authenticated if he/she correctly identifies the four faces. The technique is based on the assumption that people can recall human faces easier than other pictures. User studies by Valentine   have shown that Passfaces are very memorable over long intervals. Comparative studies conducted by Brostoff and Sasse BIB001 showed that Passfaces had only a third of the login failure rate of text-based passwords, despite having about a third the frequency of use. Their study also showed that the Passface-based login process took longer than text passwords and therefore was used less frequently by users. However the effectiveness of this method is still uncertain. Davis, et al. BIB004 studied the graphical passwords created using the Passface technique and found obvious patterns among these passwords. For example, most users tend to choose faces of people from the same race. This makes the Passface password somewhat predictable. This problem may be alleviated by arbitrarily assigning faces to users, but doing so would make it hard for people to remember the password. Jansen et al.    proposed a graphical password mechanism for mobile devices. During the enrollment stage, a user selects a theme (e.g. sea, cat, etc.) which consists of thumbnail photos and then registers a sequence of images as a password (figure 5). During the authentication, the user must enter the registered images in the correct sequence. One drawback of this technique is that since the number of thumbnail images is limited to 30, the password space is small. Each thumbnail image is assigned a numerical value, and the sequence of selection will generate a numerical password. The result showed that the image sequence length was generally shorter than the textural password length. To address this problem, two pictures can be combined to compose a new alphabet element, thus expanding the image alphabet size. Takada and Koike discussed a similar graphical password technique for mobile devices. This technique allows users to use their favorite image for authentication BIB002 . The users first register their favorite images (pass-images) with the server. During authentication, a user has to go through several rounds of verification. At each round, the user either selects a pass-image among several decoy-images or chooses nothing if no pass-image is present. The program would authorize a user only if all verifications are successful. Allowing users to register their own images makes it easier for user to remember their pass-images. A notification mechanism is also implemented to notify users when new images are registered in order to prevent unauthorized image registration. This method does not necessarily make it a more secure authentication method than text-based passwords. As shown in the studies by Davis BIB004 , users' choices of picture passwords are often predictable. Allowing users to use their own pictures would make the password even more predictable, especially if the attacker is familiar with the user.