CHAPTER - 2 Review of Literature To achieve the aim of Forensic Science, the Finger prints are considered to be one of the best evidence in linking criminals with a particular crime because they are not only unique and permanent, but also can be classified. But in large number of cases, only partial or smudged finger prints are present in which sufficient number of ridge characteristics are not present to give opinion. So there is a need to find out other characteristics which can be used in addition to ridge characteristics. The knowledge of fingerprint is quite ancient. Probably the most famous of ancient finger prints design are the carvings on the granite wall slabs of a Neolithic burial passage or dolmen, situated on an island of Brittancy, L lle de Gavr inis (Cummins, 1930; and Bridges, 1937) and referred these carvings to be of Dermatoglyphics. In 1770, Bewick engraved some of his own fingerprints as a sign of individuality and also stamped receipts with an engraved fingerprint (De Forest, 1930). Panja which include finger prints along with palm prints was used for many centuries in India as is evident from the seals found in Mohenjodaro and Harappa and our ancient texts such as Mahabharat and Ramayana (Chatterjee, 1967).The Hindus were first to classify different patterns as Chakra and Shankh etc. Faulds (1880) published an article in the scientific journal named Nature. Where he discussed fingerprints as a means of personal identification and can be used in tracing criminals from fingerprints. Then Galton in 1892 published his book Fingerprints to establish the individuality and permanence of fingerprints. He identified the characteristics by which prints can be identified. These characteristics (minutia) are still in use today and referred as Galton s Details. Schroter (1814) reported the morphology of the palmer surface and illustrated the arrangement of ridges and pores in detail.
Regarding the ridge formation no commonly accepted mechanism and topological issues exists to date and many theories and ideas have been published by many scientists (Abel, 1936, Cummins, 1926, Penrose and O Hara, 1973 and Chattopadhyay, 1975). But the folding hypothesis (that is the ridge pattern is established as the result of a folding process) was accepted by German researchers of the 1930s (Abel, 1936). Holt. (1961) attempted to study the genetic aspects of finger print patterns. Regarding another class characteristics i.e. Ridge-count comparisons has been studied in the two types of twins by certain scientists, Geipel (1941) compared the intra-pair differences in ridge-counts in 469 pairs of monozygotic twins with those of 405 pairs of same-sexed dizygotics, and 107 pairs of opposite-sexed dizygotics. The monozygotics showed a mean intra-pair difference of 11.1 + 0.4 in total ridge-count; whereas the like-sexed dizygotics showed a difference of 39.3 + 1.4; and unlike-sexed dizygotics a mean difference of 42.3 + 4.8, Newman (1930) Various scientists tried various methods for taking fingerprints and classified patterns present on the finger balls (Purkinje, 1823; Faulds, 1905; Galton, 1891& 1892; Herschel, 1894; Cummins and Midlo, 1961). Then Wentworth and Wilder, 1918; Bridges, 1963; Chatterjee, 1967; Moenssons, 1971; Cowger, 1983 and Henry and Gaensslen, 1991 further improved the work on the identification and classification of finger prints pattern types. Locard, a student of Bertillon, and the Director of the laboratory at Lyon, France, was first to establish rules for the minimum number of minutiae necessary for identification (Kingston and Kirk, 1965). He is also known as the father of Poroscopy, which is the study of pores that appear in the fingerprint ridge, and their use in the individualization process. Locard in 1912 also recognized the value of the shape of the ridge as being permanent like fingerprint, and he should also be known as the father of Edgeoscopy. Locard went beyond the variations of the individual friction ridge features which he noted, has evolved into "Ridgeology" (Ashbaugh, 1986 1991, 1994, 1995 & 1999), which is a coined phrase describing the use of those features in the fingerprint identification process. Locard should also then be known as the father of "Ridgeology". Many analysts of fingerprints consider that Edgeoscopy and Poroscopy details can be given the same weight and values as to Galton details (Moenssons, 1970 and 1975). Locard suggested that the identification could be based on the size, shape, relative position and frequency of appearance of pores. He also believed that 20-40 pores were sufficient to establish positive
identification. If eight Galton details were needed to establish individuality, then it would require a weighted value for pores (and edge details) of 1/5th for each detail observed. After that two general contributions were made to fingerprints individuality by Amy (1946) Steinwender (1958) was first to relate with precisions of the value of 12-points threshold by generalizing the thoughts of Locard. In 1962, Edgeoscopy first came to light with the paper of Chatterjee from India. He envisioned an identification process where characteristics along with the ridge would be compared and evaluated for identification purpose. He suggested various characteristics to be used for this purpose. He studied that the edges are unique and are persistent like ridges and pores. He named this method of identification as Edgeoscopy. The characteristics of the edges of the ridges do not change during the life of an individual though their size can vary with the advancement of age. He classified the characteristics of the edges of the ridges into seven classes: 1) Straight edge 2) Convex edge 3) Peaked edge 4) Table edge 5) Pocket edge 6) Concave edge 7) Angular edge These characteristics are the result of the alignment and shape of the individual ridge units as well as the pores close to the edge of the ridge. However, these shapes are only of use when the friction ridges are clearly reproduced in the latent and the exemplar prints, Kuhn, 1994 (http://www.scafo.org/library). After having been taught this concept that friction ridge skin is uniquely arranged. He did not truly understand it until being enlightened by Ridgeology (Ashbaugh, 1994 & 1999). Czarrnecki (1995) studied the aspect of Poroscopy in detail and published its relevance in an article named as Poroscopy - An overview. Hughes (1998) worked on the eight ridge characteristics in coincident sequence to make identification. He said that there could not ever be the possibility of any ridge feature being exactly the same as another.
Ashbaugh (1999) interpreted the examination of friction ridge structure in three level details. Pores have been used to assist in the matching of finger prints. Most of the matching have emphasized minutia comparison and used pores as ancillary comparison. He published a paper on Ridgeology Modern Evaluative Friction Ridge Identification for the analysis, comparison, evaluation and verification and known as A.C.E.V (Analysis, Comparison, Evaluation and Verification). The aspect of Poroscopy for personal identification was undertaken by Bindra et al. (2000) in their study rolled and plain fingerprints of one hundred individuals along with their a palm prints were obtained to study shape, size, position, interspacing and number per unit area of pores etc. these findings were compared with the findings obtained from the latent fingerprints of same number of individuals to see the practical feasibility of the Poroscopy in personal identification. Wertheim (2000) reported that if an expert ignores sweat pores and edge shapes of the ridges when they are present, it means he is ignoring valid information. But this is by no means to suggest that an expert should ignore minutiae points and concentrate on the pores and edge shapes. It is simply to say that one must consider all of the information present in both the latent print and ink print. Traditional minutiae points are still the backbone of most comparisons. He proposed a 5- step formula in which they used third level details. Observations were made on the basis of ridge shapes, pore shapes, relative positions of pores. Oliver (2002) proposed the use of third level details for the identification purposes. They joined aperture around pore together into rows forming ridges, having irregular edges and are individualistic and unique as pore and ridge characteristics. It was proposed the study of palm prints for the identification using the science of Ridgeology, Poroscopy and Edgeoscopy (Wilder, 1902; Shimoda and Franck, 1989 and Stoney and Thornton, 1986). The evaluation of the validity, reproducibility and variations in the third level of details in the population was studied by Anthonize, Aline. Observations were made to compare and classify the third level of details to demonstrate the objective of Poroscopy and Edgeoscopy in the identification purposes. Chaudhry and Kumar (2003) used lateral palm prints for the identification of author of the documents by studying Edgeoscopy and Poroscopy as patterns rarely exist at the lateral area of palm.
Poroscopy and Edgeoscopy methods were used for the purpose of personal identification by Jain et.al, 2007. They observed that the features of third level details are immutable and unique to establish the absolute identity. They design a hierarchical matching system based on high resolution fingerprints images and to maximize the performance by introducing third level details. A study was conducted by Gupta et al. in 2008 using the pore area in the latent prints developed by using Cyanoacrylate and Ninhydrin. The pores were measured by photomicrography using appropriate software tools. The data was analyzed statistically which showed that the pore area is not reproducible in the developed latent prints using either of the techniques. Gupta and Sutton (2010) studied the reproducibility of pore surface area by using direct microscopic and 500 ppi live scan images. Direct pore area measurement was shown to be difficult to estimate in 500 ppi live scan measurements owing to lack of resolution. So it is not possible to reliably use pore area as an identifying feature in fingerprint examination. Pores and ridges were automatically extracted using Gabor filters and Wevlet transformer were locally matched using the iterative closest point algorithm.