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Technology affects the communication capabilities of specialized databases in the criminal justice system in various ways. Incorporation of technology in criminal justice has made the work of criminal justice agencies easy. For instance, through the use of data transmission, the use of friendly graphics interface have enabled them to collect, analyze, as well as share the data with both inside and outside stakeholders and the government.

The use of technology has enabled the criminal justice to achieve their mission in law enforcement. Some of the notable achievements in the use of technology in criminal justice system has improved the efficiency due to the ability to store large volumes of data. As a result, intelligence and investigation have become very effective. Criminal records and other relevant data can be accessed easily.    

Technology has facilitated communication in criminal justice in passing of important information concerning a given case, as well as in resolving the complex crimes. Thus, exchange of information has undergone the major transformation within the system (Brunelli, 2009). Notably, advancement in technology has directly affected communication capabilities within the criminal justice system (Wilson, 2006). This has resulted in the use of specialized databases within the criminal justice systems to reinforce law. Some of the major databases used in criminal justice include: Automated Fingerprint Identification (AFSI) and facial recognition methods.

Automated Fingerprint Identification provides automated fingerprint to facilitate search capabilities. This system also enables latent search capability, electronic storage of images, and exchange of finger prints, as well as responses. This system enables the storage of large volume of data containing fingerprints and criminal histories of millions of suspects. On the other hand, facial recognition system involves the use of computer application that automatically identifies an individual. This is done from a digital image, as well as from a video frame where there images are retrieved from the video source (Geiger, 2011). Mainly, the facial features of a person from the image are compared with that in the database. However, other biometrics is used, such as fingerprint or an eye iris.

Live fingerprints are scanned by the use of a device Live Scan. Live Scan obtains the fingerprints by rolling or placing flat impressions on a glass platen that is above a camera unit. To match the fingerprints, the print in question is scanned. Computer algorithms are used to mark all minutia points, deltas, as well as cores present on the print. The points detected by the live scan are then reviewed to submit the feature set (Jain, 1999). Finally, the finger print image processor then assigns the quality of measure and indicates whether the finger prints are genuine or not. Facial recognition systems include the use of software, such as Google Picasa digital image organizer, Iphoto, Picture Motion Browser (PMB), windows live, as well as Facebook.

Facial recognition system identifies cases by extracting landmarks with the use of computer algorithms. For instance, algorithm has the ability to indentify size, shape, check bones, as well as jaw (Geiger, 2011). These features are feed into the databases to search for a similar person with the same features. Sometimes, the algorithm is normalized into a gallery of facial images and the data is compressed, making it possible to detect the useful data detection. New technologies in facial recognition systems involve the use of three dimensional recognition and skin texture analysis (Brunelli, 2009). In 3D, the shape of the face is taken that is used to indentify some of the distinctive features on the face, such as eye sockets, nose, as well as the chin. Skin analysis technique involves the use of visual details of the skin of an individual from a captured image by a standard digital camera. It also identifies skin lines, spots, as well as patterns in the face.

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