The study of fingerprints is centuries old and with evolving technology fingerprints have become an accurate and reliable source of human identification as well as a significant part of criminal investigations. Crucially no two individuals have exact same fingerprints. Two fingerprints are identical only if they are both produced by the same finger of the same person. Even identical twins, with identical DNA, have different fingerprints. In this article I cover the fingerprint patterns into which the forensic scientists classify fingerprints according to their characteristics, the law on fingerprints in India, and the Automated Fingerprint Identification System (AFIS) used by Investigating Agencies to store and process fingerprints.
The human fingerprint is a unique pattern that is intrinsically linked to each individual. No two fingerprints are identical, which greatly assists in its role in forensic identification. This uniqueness has allowed for various uages of fingerprinting including background checks, biometric security, mass disaster identification, and in particular criminal investigations with forensic science being increasingly used by investigating agencies in establishing the guilt of an accused as well as for exculpatory or elimination purposes. A fingerprint is a reproduction of the ridge formation of a finger on a surface. Identity is established or denied by the minutia of smaller details. The ending ridges, its bifurcations or forking, islands or enclosures, short ridges and dots that make up the patterns, and surrounding friction skin area determine whether or not a fingerprint is made by the same finger. It is not only the appearance of these details in the fingerprint but also their relative position to each other that is a major factor in the identification process.
Fingerprint analysis relies on this unique pattern with forensic scientists having categorised these patterns into distinct groups. A fingerprint classification system groups fingerprints according to their characteristics and therefore helps in the matching of a fingerprint against a large database of fingerprints.
The common terms that will be used, in brief, are as follows:
The covering of bulb of the fingers and thumbs and the palm of hands is called friction skin. The narrow elevated lines on the friction skin are called ridges and they are studded with sweat pores. The depressions between the ridges are known as furrows. The ridges are characterized by minute peculiarities such as ridge endings, bifurcations, enclosures, dots, cross overs, spurs and short ridges. Pattern is the design formed by the ridges in a fingerprint. Core is the innermost or central part or the heart of a pattern. The core of a loop fingerprint pattern may consist either of an even or uneven number of ridges called rods not joined together at the top or may consist of two ridges joined together at their summit called as staple. Whereas, in whorls pattern, circular or elliptical, the center of the first ring is the point of core. In case of spiral, the point from which the spiral begins to revolve is the point of core. The delta is a triangular plot which may be formed either by the bifurcation of a single ridge or by the divergence of two parallel ridges. The number of ridges that cut an imaginary line drawn from the delta to the core, neither the delta nor the core being counted, is known as the ridge count.
These occur in about 5% of the encountered fingerprints. An arch is also known as a pattern less pattern. It is a pattern is which the ridges of the finger run continuously from one side of the finger to the other, slightly rising in the centre, making no backward turn.
Normally, there is no delta in an arch pattern but when there is the appearance of a delta, no ridge should intervene between the delta and the core. It is then called an arch approximating loop or a loop without count.
1.1. Plain Arch
In a plain arch there is consistency of flow. It starts on one side of the finger and the ridge then slightly cascades upward. This almost resembles a wave out on the ocean and then the arch continues its journey along the finger to the other side. The plain arch pattern is the simplest of the fingerprints to discern.
1.2. Tented Arch
In tented arch, the ridges near the middle may have an upward thrust arranging themselves as it were on both sides of a spine or axis towards which adjoining ridges converge.
The difference between plain arch and tented arch is that the tented arch lies in the ridges in the centre and is not continuous like the plain arch. They have significant up thrusts in the ridges near the middle that arrange themselves on both sides of an axis. The adjoining ridges converge towards this axis and thus appear to form tents.
The loop pattern is observed in almost 60 to 70% of the fingerprints. It is a pattern in which one or more ridges enter on either side, take a diagonal upward course, recurve, touch or pass an imaginary line drawn between the delta and the core, and end or tend to end towards the same side of the pattern.
The ridges make a backward turn in loops but they do not twist. This backward turn or loop is distinguished by how the loop flows on the hand and not by how the loop flows on the card where the imprint is taken. There is one delta and a core, one recurving ridge and at least one ridge count between the delta and the core.
2.1. Ulnar Loop
Loops can be classified as ulnar where it slopes towards the ulna bone, the ulna being on the little finger side. Thus, in ulnar loops, the ridges slant towards the right in case of right-hand fingers and towards the left in case of left-hand fingers.
2.2. Radial Loop
Loops can be classified as radial where it slopes towards the radial bone, the radial being on the thumb side. Thus, in radial loops, the ridges slant towards the left in case of right-hand fingers and towards the right in case of left-hand fingers.
These can be found in about 25 to 35% of the fingerprints that are encountered. A whorl is a pattern in which one or more ridges form a series of circles or spirals around the core. The ridges in these whorls make a turn of one complete circuit with two deltas and are therefore circular or spiral in shape. Plain whorl is the simplest form of whorl and also the most common.
3.1. Central Pocket Loop Whorl
In central pocket loop whorl, the ridges immediately above the core deviate in course from the general course of other ridges, making a pocket at the center. These whorls consist of at least one re-curving ridge or an obstruction at right angles to the line of flow with two deltas so that if an imaginary line is drawn in between them no re-curving ridge within the pattern area will be touched or cut. These whorl ridges make one complete circuit and may be oval, circular, spiral or any variant of a circle.
The essential conditions of a central pocket loop whorl are there should be at least one looping ridge, the recurve about the core should be at right angles to the line of exit of the looping ridges, line joining the deltas should not cut any of the recurving ridges, and there should not be more than five recurving ridges.
3.2. Lateral Pocket Loop Whorl
When the ridges constituting the loop bend sharply on one side before recurving, thereby forming on that side an inter space or pocket usually filled by the ridges of another loop, such an impression is termed a lateral pocket loop.
3.3. Double Loop Whorl
A double loop whorl consists of two distinct and separate loop formations surrounding or encircling the other. It has two distinct and separate shoulders for each core, two deltas and one or more ridges that make a complete circuit. There is at least one re-curving ridge within the inner pattern area between the two loop formations that gets touched or cut when an imaginary line is drawn.
In lateral pocket loop, the ridges containing the points of core have their exits on the same side of either delta, while in double loop the ridges containing the points of core have their exits on different sides of either deltas.
3.4. Accidental Whorl
Accidentals are combinations of two or more patterns too irregular in outline to be grouped in any other pattern.
The composition of the pattern in accidental whorl is derived from two distinct types of patterns that have at least two deltas. Therefore, whorls containing ridges that match the characteristics of a particular whorl sub-grouping are referred to as accidental whorls.
What the law says
Fingerprints and palmprints have been widely recognized and accepted as a reliable means to identify a person. A fingerprint may be left on an object when it is touched which permits the impression to be used for personal identification of individuals in criminal investigations. Thus, the forensic science of fingerprints is utilised by law enforcement agencies in support of their investigations to positively identify the perpetrator of a crime, as well as for exculpatory or elimination purposes.
In India, the law of fingerprinting is covered by the Indian Evidence Act, 1972, the Code of Criminal Procedure, 1973 and the recent Criminal Procedure (Identification) Act, 2022.
1. Indian Evidence Act, 1872 and the Code of Criminal Procedure, 1973
Section 45 of the Indian Evidence Act, 1872 states that “when the Court has to form an opinion upon a point of foreign law or of science or art, or as identity of handwriting or finger impressions, the opinions upon that point of persons specially skilled in such foreign law, science or art, or in questions as to identity of handwriting or finger impressions are relevant facts. Such persons are called experts.”
As a general rule, the opinion of a witness on a question whether of fact or of law, is irrelevant. A witness has to state the facts which he has seen, heard or perceived, and not the conclusions which he has formed on observing or perceiving them. The function of drawing inferences from facts is a judicial function and must be performed by the Courts. If a witness is permitted to state not only the facts which he has perceived but also the opinion which he has formed on perceiving them, it would amount to delegation of judicial functions to him and investing him with the attributes of a judge.
Sections 45 to 51 of the Act are some important exceptions to this general rule. When “the subject-matter of inquiry is such that inexperienced persons are unlikely to prove capable of forming a correct judgment upon it”, or when “it so far partakes of the character of a science or art as to require a course of previous habit or study”, the opinions of persons having special knowledge of the subject-matter of inquiry become relevant; for it is very difficult for the Court to form a correct opinion on a matter of this kind, without the assistance of such persons.
Section 73 provides that the Court may direct any person present in the Court to give his/her finger impressions to enable the Court to compare such finger impressions with any other finger impressions alleged to have been made by such person.
Section 293 of the Code of Criminal Procedure, 1973 exempts Directors of Finger Print Bureau from personal appearance in the Courts for expert testimony. As long as the report of the Director of Finger Print Bureau shows that the opinion was based on observations, it can be accepted without examining the person who gave the report. But if there is any doubt, it can always be decided by the calling of the person making the report
2. The Criminal Procedure (Identification) Act, 2022
The Criminal Procedure (Identification) Act, 2022 was passed by the Lok Sabha on 4th April 2022, by the Rajya Sabha on 6th April 2022 and received the President’s assent on 18th April 2022.
The Act authorises taking measurements of convicts and other persons for the purposes of identification and investigation in criminal matters and to preserve records. It widens the power of State and its enforcement agencies during a criminal investigation, with regard to the taking of biometric and other biological data of any person arrested by the police, including persons detained under preventive detention laws. It is a modification of the Identification of Prisoners Act, 1920, which stands repealed through Section 10(1) of the 2022 Act.
Section 3 of the 2022 Act allows police officers to collect fingerprints, footprints, biological samples, behavioural attributes including signatures, handwriting and examinations under Sections 53 and 53A of the Code of Criminal Procedure, of any arrested person, including convicts. Such data also includes blood, semen, hair samples, swabs and analyses such as DNA profiling.
While the resistance or refusal to allow the taking of measurements under this Act shall be deemed to be an offence under section 186 of the Indian Penal Code, an exception also states that any person arrested under any law will not be obliged to provide such data, except when they are arrested for any offence committed against women and children or any offence punishable with imprisonment for a period not less than 7 years.
The National Crime Records Bureau (NCRB) will be the central agency to maintain the records. It will share the data with law enforcement agencies. Further, States/UTs may notify agencies to collect, preserve, and share data in their respective jurisdictions. Further, Section 4 allows the record of measurements to be retained in digital or electronic form for a period of 75 years from the date of collection of such measurement. Records will be destroyed in case of persons who are acquitted after all appeals, or released without trial. However, in such cases, a Court or Magistrate may direct the retention of details after recording reasons in writing.
Under Section 5 of the Act, a Magistrate is competent to order any person to allow his finger impressions to be taken for the purpose of any investigation or proceeding under the Code of Criminal Procedure.
Automated Fingerprint Identification System
Increase in crime together with the resultant increase in criminal records has made the manual comparison and identification of fingerprints a challenging and arduous task. The manual system of fingerprint identification was unable to keep pace with the enormous increase of the fingerprint records and the number of queries required to be answered every day. The need for an Automated Fingerprint Identification System (AFIS) was, therefore, felt by Police Officers and Fingerprint Professionals the world over.
As digital technology progresses, fingerprinting is increasingly being used as a fraud prevention measure. AFIS is a system for storing and processing digital fingerprints. By digitising the fingerprints, found traces can be compared to those recorded in the database. A fully functional AFIS provides the facilities of a database creation, an identification-oriented enquiry that includes ten print to ten print search, chance print to ten print search, ten print to chance print search, and chance print to chance print search, a remote query processing and creation of a criminal attribute database. AFIS is used mainly for two areas, the fingerprint verification and fingerprint identification. For the fingerprint identification, a found or present fingerprint is compared with the stored fingerprints in order to allow identification.
AFIS in India
In India, AFIS was first installed at the Central Finger Print Bureau of the National Crime Records Bureau in 1992. The Indian Version of AFIS is called FACTS, which was co-developed, by NCRB and CMC Ltd. India. The current version of FACTS is 5.0. The system uses image processing and pattern recognition technique to capture, encode, store and match fingerprints, including comparison of chance prints. It uses pattern class, core and delta information, minutiae location, direction, neighbouring information, ridge counts and distances, density, type, print background/foreground information etc. for matching fingerprints.
Criminal attributes such as name with aliases if any, parentage, sex, age, address etc. are also stored in the data base. The database contains all the conviction details i.e. data of conviction, Court, Section, sentence, P.S. FIR No., information regarding absconders and death reports. It has become an important aid to finger print experts in their day-to-day work of updating and querying on large database of fingerprints.
Facilities offered by AFIS
- Automated ten print search with the trace percentage not to be less than 98.
- Automated replacement of better quality prints.
- Automated pattern recognition.
- Automated ridge direction determination.
- Automated minutiae, core and delta detection and extraction.
- Automated minutiae quality assignment.
- Automated capture of logical rolled print area.
- Automated capture of logical plain print area and comparison of plain prints with rolled prints.
- Automated selection of matching digit.
- Full range of integrated chance print and ten print image enhancements.
- Manual editing of minutiae and core/delta location(s) and direction(s).
- Facility to re-edit chance print images without requiring a re-scan.
- Facility to launch secondary searches.
- Secondary/temporary database for document case examination.
- Rotation of chance print images.
- Side-by-side comparison.
- User defined search filters.
- User defined candidate thresholds.
- Integration of AFIS with personal information system.
Advantages of AFIS
- Diversifying the functioning of Finger Print Bureau through better utilization of expert manpower.
- Better management of fingerprint data.
- The entire database could be searched against chance prints.
- Replacement of poor quality prints with better quality prints.
- Less physical handling of finger print record, thus protecting original record from wear & tear.
- Matching is automatically done by the computer, at a high speed, thus substantially reducing the search time.
- Networking of AFIS at different levels possible.
- Automatic enhancement of poor quality prints.
- More accurate compilation of Statistics.
(i) Input or Acquisition or Enrolment
Flat-bed scanners are used for input of Ten Digit Record and Search Slips and Chance Prints. A unique number called the Personal Identification Number (PIN) is generated by the system and a label bearing this number is fixed to the finger print slip or behind the Chance Print photograph. The Ten-digit/Chance print is placed with the probable orientation on the scanner bed and is subjected to preview scan if required to confirm the print position followed by high resolution scanning.
Encoding takes place immediately after the high resolution scan. The features extracted by the system are:
- Pattern class and alternate pattern class
- Core and Delta points
- Minutiae (ridge end points and bifurcation points)
- Smudge area
The basic features used for finger print matching are the minutiae. Each minutiae is characterized by its coordinates, the direction of the ridge flow at the location of the minutiae, the ridge counts between itself and its nearest neighbours. The system extracts the minutiae of each fingerprint automatically. These extracted features represent the fingerprint’s uniqueness. Whenever a fingerprint is to be identified, the system compares the characteristics of the minutiae of that fingerprint against the characteristics of corresponding minutiae in each of the fingerprint in the database. The result of matching is a shortlist in the descending order of probability.
In verification, the expert compares a search finger print against short-listed finger prints from the database and identifies the right match. Finger Print images are presented to the expert in the form of split screen display – the search print on one half of the monitor and the short listed print retrieved from the system on the other. The user can select the prints from the shortlist as required. Once the expert is satisfied about the identity, he/she marks it as TRACED or else it is marked as UNTRACED.
(iv) Data Updation
Record slips are updated and stored in the database. If the finger print slip is a new one, the transaction is added to the database and is stored on hard discs. In case a duplicate is already present in the database, the system itself compares the quality of prints of both the slips and the better quality print replaces the other. The old PIN is retained.
pThe World of Fingerprinting — The Legal Conundrum
The latest findings show that with clever science, a single fingerprint left at a crime scene could be used to determine whether someone has touched or ingested class A drugs.
In a paper published in Royal Society of Chemistry’s Analyst journal, a team of researchers at the University of Surrey, in collaboration with the National Centre of Excellence in Mass Spectrometry Imaging at the National Physical Laboratory (NPL) and Ionoptika Ltd reveal how they have been able to identify the differences between the fingerprints of people who touched cocaine compared with those who have ingested the drug – even if the hands are not washed. The smart science behind the advance is the mass spectrometry imaging tools applied to the detection of cocaine and its metabolites in fingerprints.
This is a step up from research previously conducted by the University. In 2020 Surrey researchers were able to determine the difference between touch and ingestion if someone had washed their hands prior to giving a sample. Given that a suspect at a crime scene is unlikely to wash their hands before leaving fingerprints, these new findings are a significant advantage to crime forensics.
The Surrey team have continued to use their world-leading experimental fingerprint drug testing approach based on high-resolution mass spectrometry. Cocaine and its primary metabolite – benzoylecgonine*, can be imaged in fingerprints produced after either ingestion or contact with cocaine using these techniques. By analysing the images of cocaine and its metabolite in a fingerprint, and exploring the relationship between these molecules and the fingerprint ridges, it is possible to tell the difference between a person who has ingested a drug, and someone who has only touched it.
Dr Melanie Bailey, Reader in Forensic and Analytical Science and EPSRC Fellow at the University of Surrey, said: “Over the decades, fingerprinting technology has provided forensics with a great deal of information about gender and medication. Now, these new findings will inform forensics further when it comes to determining the use of class A drugs.
“In forensic science being able to understand more about the circumstances under which a fingerprint was deposited at a crime scene is important. This gives us the opportunity to reconstruct more detailed information from crime scenes in the future. The new research demonstrates that this is possible for the first time using high-resolution mass spectrometry techniques.”
Dr Allen Bellew, Applications & Marketing Manager at Ionoptika, commented: “To image these metabolites excreted through the skin requires very powerful analytical tools such as the unique Water Cluster Source that Ionoptika has been developing for over a decade. It’s clear that this new technique will be important for forensic science in the future, and as a small business in the UK it’s very exciting to see the role that our J105 SIMS instrument has played in its development.”
Dr Chelsea Nikula, Higher Research Scientist, NPL said: “This novel application of three different techniques illustrates the capabilities of mass spectrometry imaging to enable next-generation forensics analyses. It is great to see that the work we do here at NPL and the facilities we have available to us at the National Centre of Excellence in Mass Spectrometry Imaging helped support this research.”
*Benzoylecgonine is a molecule produced in the body when cocaine is ingested, and it is essential in distinguishing those who have consumed the class A drug from those who have handled it.
Provided by University of Surrey
The latest findings show that with clever science, a single fingerprint left at a crime scene could be used to determine whether someone has touched or ingested class A drugs. In a paper published in Royal Society of Chemistry’s Analyst journal, a team of researchers at the University of Surrey, in collaboration with the National Centre […]Single Fingerprint At A Crime Scene Detects Class A Drug Usage (Forensic Science) — Uncover reality
Everything we touched, leave behind our unique impression on it, which is Our fingerprints.
No two people have exactly the same fingerprints. Even identical twins, with identical DNA, have different fingerprints.
Fingerprint identification also known as “Dactyloscopy”.
Fingerprints are the tiny ridges, whorls and valley patterns on the tip of each fingers. They develop from pressure on a baby’s tiny, developing fingers in the womb.
CLASSIFICATION OF FINGERPRINTS
By FRANCIS GALTON
A well-known British scientist sir Francis Galton published his first book on fingerprint in 1892. His important work include method for classification for fingerprint which are divided into three groups-
By WILLIAM J. HERSHEL
While working for the East India Company in Bengal, India, Sir William James Herschel first used fingerprints on native contracts. After a decade, he had accumulated a file of fingerprints.
By EDWARD HENRY
Henry Classification of Fingerprinting was accepted as common practice throughout England and its territorial holdings and in the United States.
Under the henry system, fingerprints divided into two classes:
•Those which are given numerical value. (whorls and composites).
•Those which doesn’t give numerical value. (loops and arches).
All patters are divided as follows:
The henry classification system assigns each finger A number according to the order in which it is located in the hand, beginning with the right thumb as number 1 and ending with the left pinky as number 10.
• The system also assigns a numerical value to fingers that contain a whorl pattern; fingers 1 and 2 each have a value of 16,
• Fingers 3 and 4 = 8,
• Fingers 5 and 6 = 4,
• Fingers 7 and 8 = 2,
• Final two fingers = 1.
• Fingers with a non-whorl pattern, such as an arch or loop pattern, have a value of zero.
• The sum of the even finger value is then calculated and placed in the numerator of a fraction.
• The sum of the odd finger values is place in the denominator.
• The value of 1 is added to each sum of the whorls with the maximum obtainable on either side of the fraction begin 32.
• Thus, the primary classification is a fraction between 1/1 to 32/32, where 1/1 would indicate no whorl patterns and 32/32 would mean that all fingers had whorl patterns.
By JUAN VUCETICH
Vucetich is credited with the first positive criminal identification as, in 1892, he was able to extract a set of prints off a door and thus identify a woman as the culprit in a double homicide.
CHARACTERISTICS OF FINGERPRINT
Class characteristics are the characteristics that narrow the print down to a group but not an individual.
The Three Fingerprint Class Types Are;
Arches are the simplest type of fingerprints that are formed by ridges that enter on one side of the print and exit on the other. No deltas are present.
About 5 % of the world’s populations have arch patterns.
Loops must have one delta and one or more ridges that enter and leave on the same side. These patterns are named for their positions related to the radius and ulna bones.
About 60-65 % of the world’s populations have loop patterns.
Whorls have at least one ridge that makes (or tends to make) a complete circuit. They also have at least two deltas.
About 30-35 % of the world’s populations have whorls patterns.
Individual characteristics are those characteristics that are unique to an individual.
They are tiny irregularities that appear within the friction ridges and are referred to as Galton’s details.
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By @forensicfield INTRODUCTION Everything we touched, leave behind our unique impression on it, which is Our fingerprints. No two people have exactly the same fingerprints. Even identical twins, with identical DNA, have different fingerprints. Fingerprint identification also known as “Dactyloscopy”. Fingerprints are the tiny ridges, whorls and valley patterns on the tip of each fingers. […]