Automated Fingerprint Identification Systems (AFIS).pptx

Automated Fingerprint Identification Systems (AFIS) have revolutionized the field of forensic science and biometric identification. The foundation of AFIS is the unique nature of fingerprints, which remain unchanged throughout a person's life and are distinct for each individual. AFIS utilizes this uniqueness to store, process, and compare fingerprint data electronically. The history of AFIS dates back to the late 1960s and early 1970s when law enforcement agencies recognized the need for a more efficient way to handle fingerprint records. Before AFIS, fingerprint identification was a manual process that required forensic experts to painstakingly compare prints by hand, which was time-consuming and prone to errors.

AFIS brought a paradigm shift by introducing automated processes for capturing, storing, and comparing fingerprint images. The system works by converting the physical characteristics of a fingerprint into a digital format through scanning or digital capture methods. These digital fingerprints are then processed using complex algorithms to extract unique features, such as ridge endings and bifurcations, known as minutiae points. These features are stored in a digital database, which can be searched and compared against new fingerprint inputs. The system's speed and accuracy are unparalleled, capable of matching fingerprints within seconds, even in databases containing millions of records.

One of the most significant advantages of AFIS is its ability to operate in real-time, providing law enforcement agencies with the capability to quickly identify individuals during routine checks, criminal investigations, and border control operations. The system can perform one-to-one matches to verify an individual's identity or one-to-many matches to identify an unknown fingerprint against a vast database. This dual functionality makes AFIS a versatile tool in various applications, from solving crimes to securing sensitive facilities.

Forensic experts and criminologists have praised AFIS for its role in solving cold cases and linking suspects to multiple crime scenes. The system's ability to match latent prints found at crime scenes to known prints in the database has led to numerous breakthroughs in previously unsolved cases. In addition to its forensic applications, AFIS is also used in civil identification programs, such as background checks for employment, voter registration, and welfare disbursement, ensuring that individuals are who they claim to be.
The implementation of AFIS requires a significant investment in technology and infrastructure, but the benefits far outweigh the costs. Modern AFIS systems are equipped with advanced features like mobile fingerprint scanners, cloud-based databases, and integration with other biometric systems like facial recognition and iris scanning. These advancements have further enhanced the efficiency and effectiveness of AFIS, making it an indispensable tool in modern law enforcement

1. Automated Fingerprint Identification Systems (AFIS) RISHAB M NAIR MSC FORENSIC SCIENCE

2. WHAT IS AFIS ? The Automated Fingerprint Identification System (AFIS) is a biometric technology that digitally stores representations of friction ridge skin, such as fingerprints , palmprints , and footprints . It enables rapid database searches to identify connections between different impressions. AFIS offers an electronic database that simplifies the maintenance of accurate records and allows for quick access to relevant information AFIS can rapidly search through millions of fingerprints in seconds, facilitating large-scale searches and the automated identification of potential suspects It is primarily utilized for identifying individuals in contexts such as border control and visa applications , as well as linking an individual to a mark in criminal investigations or public inquiries. The enrollment of individuals can be entirely digital through Live Scan , with biometric feature extraction and encoding fully automated . This system also facilitates the sharing of fingerprint data across different agencies and jurisdictions , enhancing collaboration and increasing the likelihood of identifying unknown individuals and solving crimes. The  National Automated Fingerprint Identification System (NAFIS)  is a centralized database developed by the National Crime Records Bureau (NCRB) in India.   It aims to consolidate fingerprint data from all states and union territories into a single, searchable national database

3. HISTORY OF AFIS Historical Context : Law enforcement agencies historically employed fingerprint examiners for manual classification, filing, and searching. FBI’s Identification Division : Established in 1924, initially contained 810,188 fingerprint records, processing about 30,000 tenprint cards daily.. Development of AFIS : Automated Fingerprint Identification System (AFIS) was developed to address this problem. Capabilities of Computers : Computers store vast amounts of information, perform multiple functions simultaneously, and operate continuously. Royal Canadian Mounted Police : Implemented an automated system in 1977. San Francisco’s Initiative : First U.S. jurisdiction to routinely use AFIS in 1983, following 80% citizen approval. Crime Scene Investigations Unit : Formed in San Francisco, leading to a tenfold increase in fingerprint identifications and a 26% decrease in burglary rates over four years. Global Adoption : Countries like the U.S., France, Canada, the U.K., and Japan developed computer systems for identification bureaus. Routine Use Today : Most law enforcement agencies now routinely use AFIS for criminal investigations NGI System : By 2012, the FBI’s Next Generation Identification (NGI) system contained over 70 million criminal files and more than 700 million individual fingerprints. (Formerly known as iAFIS )

4. AFIS DATABASE AND STORAGE SYSTEM

5. TYPES OF FINGERPRINTS PROCESSED BY AFIS

6. GENRAL WORKFLOW OF AFIS

7. steps for processing a fingerprint search using AFIS: Transfer of Marks : Marks recovered from crime scenes are sent to the fingerprint office either physically (as a lift) or digitally (as an image). Initial Assessment : An examiner assesses the mark to determine if it meets the agency’s requirements for an AFIS search. Upload to AFIS : If suitable, the mark is uploaded to AFIS with relevant case information via digital scan or file. Orientation : The examiner orients the mark in the upright position as it appears on the reference set. If the region of the mark is identifiable (e.g., left thumb), the examiner can nominate the specific region for the search. Encoding of Features : The mark is encoded by extracting features such as ridge endings and bifurcations. Encoding can be done manually, automatically, or in combination. Creation of Feature Map : Encoded features create a map based on geometric relationships and spatial frequency between minutiae. Search Initiation : The encoded mark is launched for search in the AFIS database.

8. steps for processing a fingerprint search using AFIS: Generation of Candidate List : AFIS generates a list of biometric candidates based on the similarity between the mark and reference prints. Comparison and Evaluation : The search results are categorized as either a hit or no hit. Examiners typically manually compare the top 10 to 20 candidates to reach a decision. Biometric Recognition : A positive comparison decision implies the mark and print are from the same source. A negative comparison decision implies they are not from the same source. Handling Non-Recognition : If the mark is not recognized, it may be because the individual’s fingerprint reference set is not in the database.

9. AUTO-ENCONDING MANUAL-ENCODING Automated extraction and annotation of fingerprint features. Typically involves minimal to no human intervention. Often referred to as “lights-out” processing. Human examiners manually extract and annotate fingerprint features. Involves detailed analysis and interpretation by trained professionals. Very fast, capable of processing a single fully rolled fingerprint containing between 40 and 100 minutiae quickly. Supports faster turnaround times (TATs) for high-clarity marks. Time-consuming, especially for complete reference sets. Slower compared to auto-encoding due to the manual effort involved. Requires fewer human resources, making it cost-effective. Ideal for processing large volumes of fingerprints More costly due to the need for skilled examiners. Labor-intensive, requiring significant human resources. Provides consistent results as it eliminates human error and variability. Standardized processing across all fingerprints. Allows for expert judgment and handling of complex or low-quality prints. Can adapt to unique or challenging fingerprint patterns. Commonly used during the enrollment of biometric reference sets. Suitable for high-clarity marks that require minimal human intervention. Often used for low-quality or smudged prints where automated systems may struggle Essential for detailed forensic analysis and verification.

10. forensic science in AFIS:

11. CHALLENGES AND limitations of afis Quality of Fingerprints : Low-Quality Prints : Smudged, partial, or low-quality prints can reduce the accuracy of matches Environmental Factors : Conditions under which fingerprints are collected (e.g., weather, surface type) can affect quality Cost : High Implementation Costs : Setting up and maintaining AFIS can be expensive, limiting its adoption to well-funded agencies Operational Costs : Ongoing costs for updates, maintenance, and training can be substantial Human Factors : Expertise Required : Skilled examiners are needed to handle complex cases and verify matches Human Errors : Human errors can affect the accuracy of manual reviews Technological Limitations : Algorithm Limitations : Even advanced algorithms may struggle with highly distorted or incomplete prints Hardware Dependence : The performance of AFIS is dependent on the quality and capability of the hardware used Legal and Policy Issues : Regulatory Compliance : Ensuring compliance with various national and international regulations can be challenging Retention Policies : Policies regarding the retention and use of fingerprint data can vary, affecting how long data is stored and used

12. CHALLENGES AND LIMITATIONS OF AFIS Data Privacy and Security : Sensitive Information : Handling and storing biometric data raises privacy concerns Security Risks : Protecting the database from cyber-attacks and unauthorized access is critical Motivational Bias : Close Connectivity with Investigators : Examiners may be influenced by their relationship with investigators. Desire for Positive Outcomes : Examiners may feel pressured to reach positive comparison decisions to gain recognition or assist police informants. Task-Irrelevant Information : Dual Functions : Examiners who both process crime scenes and search for marks may be exposed to task-irrelevant information. Influence on Judgment : Knowledge of a suspect’s criminal history or alibi can unconsciously influence examiners’ decisions. Legal and Ethical Standards : Compliance with Laws : Ensuring that the use of AFIS complies with national and international laws and regulations is crucial. This includes data protection laws and human rights standards. Ethical Guidelines : Developing and adhering to ethical guidelines for the use of biometric data can help address concerns and build public trust.

13. Advancement of afis Advanced Image Processing : Image Enhancement : New image processing techniques enhance the quality of fingerprint images, making it easier to extract and analyze features 3D Fingerprint Scanning : Emerging technologies like 3D fingerprint scanning provide more detailed and accurate representations of fingerprints, improving the reliability of matches Cloud-Based Solutions : Scalability : Cloud-based AFIS solutions offer scalable storage and processing capabilities, allowing agencies to handle larger databases without significant infrastructure investments Accessibility : Cloud solutions enable remote access to AFIS databases, facilitating real-time data sharing and collaboration across different locations Multimodal Biometric Identification Systems (MBIS) : Combining Modalities : MBIS integrates multiple biometric modalities, such as fingerprints, iris scans, and facial recognition, to provide a more comprehensive identification system Enhanced Accuracy : By combining different biometric data points, MBIS improves the accuracy and reliability of identifications

14. ADVANCEMENT OF AFIS Mobile AFIS : Field Access : Mobile AFIS solutions allow law enforcement officers to capture and search fingerprints in the field using portable devices This capability is particularly useful for rapid identification during investigations and at border control points. Real-Time Results : Mobile AFIS provides real-time results, enabling officers to make quick decisions based on accurate biometric data Artificial Intelligence and Machine Learning : Predictive Analytics : AI and machine learning algorithms can predict and identify patterns in fingerprint data, improving the accuracy and efficiency of searches . Continuous Learning : These technologies enable AFIS systems to continuously learn and adapt, enhancing their performance over time Applications Beyond Law Enforcement : Civil Applications : Integrated biometric systems are used in various civil applications, such as border control, visa applications, and national ID programs Public Safety and Security : These systems enhance public safety and security by providing accurate and reliable identification methods

15. Case study Case Background In 2006, a brutal dacoity and murder occurred in a residential area of Delhi. Despite extensive investigations, the case went cold due to a lack of concrete evidence and leads. The crime scene had several fingerprints, but without a centralized database, matching them to potential suspects was challenging. Breakthrough with NAFIS In 2023, the Delhi Police revisited the case using the National Automated Fingerprint Identification System (NAFIS). Here’s how NAFIS played a crucial role: Digitization of Fingerprints : The fingerprints collected from the crime scene in 2006 were digitized and uploaded into the NAFIS database. Automated Matching : NAFIS used advanced algorithms to compare the uploaded fingerprints with millions of records in the database. This process, which would have taken months manually, was completed in a matter of hours. Identification : The system identified a match with a known criminal who had been arrested for a minor offense in another state. His fingerprints were in the database due to prior arrests. Verification and Validation : The match was verified by forensic experts to ensure accuracy. The suspect’s background was checked, revealing a history of similar crimes. Arrest and Conviction With the suspect identified, the police tracked him down and arrested him. During interrogation, he confessed to the crime, providing details that matched the evidence collected in 2006. The case was finally solved, bringing closure to the victims’ families. Impact of NAFIS This case highlights the transformative impact of NAFIS on forensic investigations in India. By centralizing and automating fingerprint data, NAFIS has made it possible to solve cold cases and bring criminals to justice more efficiently.

16. REFERENCE AFIS: History of biometrics & forensics (June 2023) (thalesgroup.com) AFIS (Automated Fingerprint Identification System) - FAQs (innovatrics.com) Toward better AFIS practice and process in the forensic fingerprint environment- Toward better AFIS practice and process in the forensic fingerprint environment - ScienceDirect https://darpg-innovation.nic.in/uploads/5wuevudtOKNAFIS.pdf Moses Daluz , H. (2018). Fundamentals of Fingerprint Analysis, Second Edition (2nd ed.). CRC Press. https://doi.org/10.4324/9781351043205