Automatic segmentation of latent fingerprints

Latent fingerprints are routinely found at crime scenes due to the inadvertent contact of the criminals' finger tips with various objects. As such, they have been used as crucial evidence for identifying and convicting criminals by law enforcement agencies. However, compared to plain and rolled prints, latent fingerprints usually have poor quality of ridge impressions with small fingerprint area, and contain large overlap between the foreground area (friction ridge pattern) and structured or random noise in the background. Accordingly, latent fingerprint segmentation is a difficult problem. In this paper, we propose a latent fingerprint segmentation algorithm whose goal is to separate the fingerprint region (region of interest) from background. Our algorithm utilizes both ridge orientation and frequency features. The orientation tensor is used to obtain the symmetric patterns of fingerprint ridge orientation, and local Fourier analysis method is used to estimate the local ridge frequency of the latent fingerprint. Candidate fingerprint (foreground) regions are obtained for each feature type; an intersection of regions from orientation and frequency features localizes the true latent fingerprint regions. To verify the viability of the proposed segmentation algorithm, we evaluated the segmentation results in two aspects: a comparison with the ground truth foreground and matching performance based on segmented region. © 2012 IEEE.

Fusão de métodos baseados em minúcias e em cristas para reconhecimento de impressões digitais

Pós-graduação em Ciência da Computação - IBILCE

Fingerprint analysis using wavelet transform with application to compression and feature extraction

The main goal of this research is to design an efficient compression al~ gorithm for fingerprint images. The wavelet transform technique is the principal tool used to reduce interpixel redundancies and to obtain a parsimonious representation for these images. A specific fixed decomposition structure is designed to be used by the wavelet packet in order to save on the computation, transmission, and storage costs. This decomposition structure is based on analysis of information packing performance of several decompositions, two-dimensional power spectral density, effect of each frequency band on the reconstructed image, and the human visual sensitivities. This fixed structure is found to provide the "most" suitable representation for fingerprints, according to the chosen criteria. Different compression techniques are used for different subbands, based on their observed statistics. The decision is based on the effect of each subband on the reconstructed image according to the mean square criteria as well as the sensitivities in human vision. To design an efficient quantization algorithm, a precise model for distribution of the wavelet coefficients is developed. The model is based on the generalized Gaussian distribution. A least squares algorithm on a nonlinear function of the distribution model shape parameter is formulated to estimate the model parameters. A noise shaping bit allocation procedure is then used to assign the bit rate among subbands. To obtain high compression ratios, vector quantization is used. In this work, the lattice vector quantization (LVQ) is chosen because of its superior performance over other types of vector quantizers. The structure of a lattice quantizer is determined by its parameters known as truncation level and scaling factor. In lattice-based compression algorithms reported in the literature the lattice structure is commonly predetermined leading to a nonoptimized quantization approach. In this research, a new technique for determining the lattice parameters is proposed. In the lattice structure design, no assumption about the lattice parameters is made and no training and multi-quantizing is required. The design is based on minimizing the quantization distortion by adapting to the statistical characteristics of the source in each subimage. 11 Abstract Abstract Since LVQ is a multidimensional generalization of uniform quantizers, it produces minimum distortion for inputs with uniform distributions. In order to take advantage of the properties of LVQ and its fast implementation, while considering the i.i.d. nonuniform distribution of wavelet coefficients, the piecewise-uniform pyramid LVQ algorithm is proposed. The proposed algorithm quantizes almost all of source vectors without the need to project these on the lattice outermost shell, while it properly maintains a small codebook size. It also resolves the wedge region problem commonly encountered with sharply distributed random sources. These represent some of the drawbacks of the algorithm proposed by Barlaud [26). The proposed algorithm handles all types of lattices, not only the cubic lattices, as opposed to the algorithms developed by Fischer [29) and Jeong [42). Furthermore, no training and multiquantizing (to determine lattice parameters) is required, as opposed to Powell's algorithm [78). For coefficients with high-frequency content, the positive-negative mean algorithm is proposed to improve the resolution of reconstructed images. For coefficients with low-frequency content, a lossless predictive compression scheme is used to preserve the quality of reconstructed images. A method to reduce bit requirements of necessary side information is also introduced. Lossless entropy coding techniques are subsequently used to remove coding redundancy. The algorithms result in high quality reconstructed images with better compression ratios than other available algorithms. To evaluate the proposed algorithms their objective and subjective performance comparisons with other available techniques are presented. The quality of the reconstructed images is important for a reliable identification. Enhancement and feature extraction on the reconstructed images are also investigated in this research. A structural-based feature extraction algorithm is proposed in which the unique properties of fingerprint textures are used to enhance the images and improve the fidelity of their characteristic features. The ridges are extracted from enhanced grey-level foreground areas based on the local ridge dominant directions. The proposed ridge extraction algorithm, properly preserves the natural shape of grey-level ridges as well as precise locations of the features, as opposed to the ridge extraction algorithm in [81). Furthermore, it is fast and operates only on foreground regions, as opposed to the adaptive floating average thresholding process in [68). Spurious features are subsequently eliminated using the proposed post-processing scheme.

Fingerprint analysis of eucommia bark by LC-DAD and LC-MS with the aid of chemometrics

Chromatographic fingerprints of 46 Eucommia Bark samples were obtained by liquid chromatography-diode array detector (LC-DAD). These samples were collected from eight provinces in China, with different geographical locations, and climates. Seven common LC peaks that could be used for fingerprinting this common popular traditional Chinese medicine were found, and six were identified as substituted resinols (4 compounds), geniposidic acid and chlorogenic acid by LC-MS. Principal components analysis (PCA) indicated that samples from the Sichuan, Hubei, Shanxi and Anhui—the SHSA provinces, clustered together. The other objects from the four provinces, Guizhou, Jiangxi, Gansu and Henan, were discriminated and widely scattered on the biplot in four province clusters. The SHSA provinces are geographically close together while the others are spread out. Thus, such results suggested that the composition of the Eucommia Bark samples was dependent on their geographic location and environment. In general, the basis for discrimination on the PCA biplot from the original 46 objects× 7 variables data matrix was the same as that for the SHSA subset (36 × 7 matrix). The seven marker compound loading vectors grouped into three sets: (1) three closely correlating substituted resinol compounds and chlorogenic acid; (2) the fourth resinol compound identified by the OCH3 substituent in the R4 position, and an unknown compound; and (3) the geniposidic acid, which was independent of the set 1 variables, and which negatively correlated with the set 2 ones above. These observations from the PCA biplot were supported by hierarchical cluster analysis, and indicated that Eucommia Bark preparations may be successfully compared with the use of the HPLC responses from the seven marker compounds and chemometric methods such as PCA and the complementary hierarchical cluster analysis (HCA).

Quality evaluation of Yin Chen Hao Tang extract based on fingerprint chromatogram and simultaneous determination of five bioactive constituents

A completely validated method based on HPLC coupled with photodiode array detector (HPLC-UV) was described for evaluating and controlling quality of Yin Chen Hao Tang extract (YCHTE). First, HPLC-UV fingerprint chromatogram of YCHTE was established for preliminarily elucidating amount and chromatographic trajectory of chemical constituents in YCHTE. Second, for the first time, five mainly bioactive constituents in YCHTE were simultaneously determined based on fingerprint chromatogram for furthermore controlling the quality of YCHTE quantitatively. The developed method was applied to analyze 12 batches of YCHTE samples which consisted of herbal drugs from different places of production, showed acceptable linearity, intraday (RSD <5%), interday precision (RSD <4.80%), and accuracy (RSD <2.80%). As a result, fingerprint chromatogram determined 15 representative general fingerprint peaks, and the fingerprint chromatogram resemblances are all better than 0.9996. The contents of five analytes in different batches of YCHTE samples do not indicate significant difference. So, it is concluded that the developed HPLC-UV method is a more fully validated and complete method for evaluating and controlling the quality of YCHTE.

Anatomy of sand beach ridges : evidence from severe Tropical Cyclone Yasi and its predecessors, northeast Queensland, Australia

[1] Four well-identified tropical cyclones over the past century have been responsible for depositing distinct units of predominantly quartzose sand and gravel to form the most seaward beach ridge at several locations along the wet tropical coast of northeast Queensland, Australia. These units deposited by tropical cyclones display a key sedimentary signature characterized by a sharp basal erosional contact, a coarser grain size than the underlying facies and a coarse-skewed trend toward the base. Coarse-skewed distributions with minimal change in mean grain size also characterize the upper levels of the high-energy deposited units at locations within the zone of maximum onshore winds during the tropical cyclone. These same coarse skew distributions are not apparent in sediments deposited at locations where predominantly offshore winds occurred during the cyclone, which in the case of northeast Australia is north of the eye-crossing location. These sedimentary signatures, along with the geochemical indicators and the degraded nature of the microfossil assemblages, have proven to be useful proxies to identify storm-deposited units within the study site and can also provide useful proxies in older beach ridges where advanced pedogenesis has obscured visual stratigraphic markers. As a consequence, more detailed long-term histories of storms and tropical cyclones can now be developed.

Feature extraction for fingerprint classification

This paper presents two algorithms for smoothing and feature extraction for fingerprint classification. Deutsch's(2) Thinning algorithm (rectangular array) is used for thinning the digitized fingerprint (binary version). A simple algorithm is also suggested for classifying the fingerprints. Experimental results obtained using such algorithms are presented.

Defective in Cuticular Ridges (DCR) of Arabidopsis thaliana, a Gene Associated with Surface Cutin Formation, Encodes a Soluble Diacylglycerol Acyltransferase

A key step in the triacylglycerol (TAG) biosynthetic pathway is the final acylation of diacylglycerol (DAG) by DAG acyltransferase. In silico analysis has revealed that the DCR (defective in cuticular ridges) (At5g23940) gene has a typical HX4D acyltransferase motif at the N-terminal end and a lipid binding motif VX(2)GF at the middle of the sequence. To understand the biochemical function, the gene was overexpressed in Escherichia coli, and the purified recombinant protein was found to acylate DAG specifically in an acyl-CoA-dependent manner. Overexpression of At5g23940 in a Saccharomyces cerevisiae quadruple mutant deficient in DAG acyltransferases resulted in TAG accumulation. At5g23940 rescued the growth of this quadruple mutant in the oleate-containing medium, whereas empty vector control did not. Lipid particles were localized in the cytosol of At5g23940-transformed quadruple mutant cells, as observed by oil red O staining. There was an incorporation of 16-hydroxyhexadecanoic acid into TAG in At5g23940-transformed cells of quadruple mutant. Here we report a soluble acyl-CoA-dependent DAG acyltransferase from Arabidopsis thaliana. Taken together, these data suggest that a broad specific DAG acyltransferase may be involved in the cutin as well as in the TAG biosynthesis by supplying hydroxy fatty acid.

FIVDL: Fingerprint Image Verification using Dictionary Learning

Fingerprints are used for identification in forensics and are classified into Manual and Automatic. Automatic fingerprint identification system is classified into Latent and Exemplar. A novel Exemplar technique of Fingerprint Image Verification using Dictionary Learning (FIVDL) is proposed to improve the performance of low quality fingerprints, where Dictionary learning method reduces the time complexity by using block processing instead of pixel processing. The dynamic range of an image is adjusted by using Successive Mean Quantization Transform (SMQT) technique and the frequency domain noise is reduced using spectral frequency Histogram Equalization. Then, an adaptive nonlinear dynamic range adjustment technique is utilized to determine the local spectral features on corresponding fingerprint ridge frequency and orientation. The dictionary is constructed using spatial fundamental frequency that is determined from the spectral features. These dictionaries help in removing the spurious noise present in fingerprints and reduce the time complexity by using block processing instead of pixel processing. Further, dictionaries are used to reconstruct the image for matching. The proposed FIVDL is verified on FVC database sets and Experimental result shows an improvement over the state-of-the-art techniques. (C) 2015 The Authors. Published by Elsevier B.V.

Donut-Shaped Fingerprint In Homologous Polypeptide Relationships-A Topological Feature Related To Pathogenic Structural Changes In Conformational Disease

Features of homologous relationship of proteins can provide us a general picture of protein universe, assist protein design and analysis, and further our comprehension of the evolution of organisms. Here we carried Out a Study of the evolution Of protein molecules by investigating homologous relationships among residue segments. The motive was to identify detailed topological features of homologous relationships for short residue segments in the whole protein universe. Based on the data of a large number of non-redundant Proteins, the universe of non-membrane polypeptide was analyzed by considering both residue mutations and structural conservation. By connecting homologous segments with edges, we obtained a homologous relationship network of the whole universe of short residue segments, which we named the graph of polypeptide relationships (GPR). Since the network is extremely complicated for topological transitions, to obtain an in-depth understanding, only subgraphs composed of vital nodes of the GPR were analyzed. Such analysis of vital subgraphs of the GPR revealed a donut-shaped fingerprint. Utilization of this topological feature revealed the switch sites (where the beginning of exposure Of previously hidden "hot spots" of fibril-forming happens, in consequence a further opportunity for protein aggregation is Provided; 188-202) of the conformational conversion of the normal alpha-helix-rich prion protein PrPC to the beta-sheet-rich PrPSc that is thought to be responsible for a group of fatal neurodegenerative diseases, transmissible spongiform encephalopathies. Efforts in analyzing other proteins related to various conformational diseases are also introduced. (C) 2009 Elsevier Ltd. All rights reserved.

Importance of shoreface sand ridges as habitat for fishes off the northeast coast of the United States

To determine if shoreface sand ridges provide unique habitats for fish on the inner continental shelf, two cross-shelf trawl surveys (23 km in length) were conducted in southern New Jersey (July and September 1991−95 with a beam trawl and July and September 1997−06 with an otter trawl) to assess whether species abundance, richness, and assemblages differed on and away from the ridge. The dominant species collected with both gears were from the families Paralichthyidae, Triglidae, Gobiidae, Serranidae, Engraulidae, Stromateidae, and Sciaenidae. Overall abundance (n=41,451 individuals) and species richness (n=61 species) were distributed bimodally across the nearshore to offshore transect, and the highest values were found on either side of the sand ridge regardless of gear type. Canonical correspondence analysis revealed three species assemblages: inshore (<5 meters depth), near-ridge (9−14 meters depth), and offshore (>14 meters depth), and variation in species composition between gear types. Environmental factors that corresponded with the assemblage changes included depth, temperature, distance from the top of the ridge, and habitat complexity. The most abundant near-ridge assemblages were distinct and included economically important species. Sand ridges of the inner continental shelf appear to be important habitat for a number of fish species and therefore may not be a suitable area for sand and gravel mining.