• Analytical Science and Technology
• /
• v.30 no.5
• /
• pp.279-286
• /
• 2017

Determination of the order of latent fingerprints deposition on the surface of thermal paper, often found in crime scenes, is related to the study of time course and aging of fingerprints and can provide additional information in criminal investigations. A preliminary study was performed to determine the deposition order of fingerprints left with two different conditions of deposition pressure and time (in seconds) after 1 day intervals for 7 days on thermal paper (receipt and fax thermal paper) using an iodine fuming method. The resultant images of the visualized fingerprints were analyzed with densitometric image analysis to measure the changes in the areas of the ridges, which can be correlated to the deposition order. No significant variation was found with the different types of thermal paper. The average areas of the friction ridges increased gradually or were similar to the values from day 1 for 3 days, and then a continual decrease was shown from day 4 through day 7. The area values from day 6 and day 7 were less than half of those from day 1. Furthermore, the test with overlapped fingerprints showed the possibility of differentiation between fingerprints that are 1-3 and 6-7 days old based on the clarity visible to the naked eye. Additional experiments with the deposition conditions can prove that the current method is valuable for the determining the order of fingerprint deposition on thermal paper.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.5
• /
• pp.2339-2345
• /
• 2011

Gait recognition is the method to identify the person who walks in front of camera using characteristics of individuals by a sequence of images of walking people. The accuracy of biometric such as fingerprint or iris is very high; however, to provide information needs downsides which allow users to direct contact or close-up, etc. There have been many studies in gait recognition because it could capture images and analysis characteristics far from a person. In order to recognize the gait of person needs a continuous sequence of walking which can be distinguished from the individuals should be extracted features rather than an single image. Therefore, this paper proposes a method of gait recognition that the motion of objects in sequence is described the characteristics of a shape sequence descriptor, and through a variety of experiments can show possibility as a recognition technique.

• Journal of the Institute of Convergence Signal Processing
• /
• v.15 no.4
• /
• pp.135-140
• /
• 2014

As the digital image devices are widely used, interests in the software- and the hardware-related image processing become higher and the image processing techniques are applied in various fields such as object recognition, object detection, fingerprint recognition, and etc. For the edge detections Sobel, Prewitt, Laplacian, Roberts and Canny detectors are used and these existing methods can excellently detect the edges of the images without noise. However, in the images corrupted by the impulse noise, these methods are insufficent in noise elimination characteristics, showing unsatisfactory edge detection. Therefore in this paper, in order to obtain excellent edge detection characteristics in the corrupted image by the impulse noise, an detection algorithm is porposed, which uses the central pixel of mask divided by four regions along the axis, calculates the estimated mask according to the representing pixel values in each regions, and detects the final edges by applying the estimates mask and the new directional one.

• Journal of the Korea Computer Industry Society
• /
• v.3 no.9
• /
• pp.1269-1278
• /
• 2002

The more high growth of knowledge, the more need personal identity technique. Fingerprint or iris of the eye identity techniques are already commercialized and used various field. Using human face recognition or authentication are not high performance yet. But application for an organism or face recognition are expected getting important. We propose a user recognition system by verifying similarity comparison of eye and lip component images which are splitted, calculated characteristic rate of each facial components and added weight to special formula. Through test proposed methods and analysis the result, we got a high recognition rate.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.12
• /
• pp.6152-6168
• /
• 2017

Recently, the biometric-based authentication systems such as FIDO (Fast Identity Online) are increased in mobile computing environments. The biometric-based authentication systems are performed on the mobile devices with the battery, the improving energy efficiency is important issue. In the case, the size of images (i.e., face, fingerprint, iris, and etc.) affects both recognition accuracy and energy consumption, and hence the tradeoff analysis between the both recognition accuracy and energy consumption is necessary. In this paper, we propose an energy-efficient way to authenticate based on biometric information with tradeoff analysis between the both recognition accuracy and energy consumption in multimedia IoT (Internet of Things) transmission environments. We select the facial information among biometric information, and especially consider the multicore-based mobile devices. Based on our experimental results, we prove that the proposed approach can enhance the energy efficiency of GABOR+LBP+GRAY VALUE, GABOR+LBP, GABOR, and LBP by factors of 6.8, 3.6, 3.6, and 2.4 over the baseline, respectively, while satisfying user's face recognition accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.1
• /
• pp.454-475
• /
• 2018

This paper presents a novel Android malware classification model planned to classify and categorize Android malicious code at Drebin dataset. The amount of malicious mobile application targeting Android based smartphones has increased rapidly. In this paper, Restricted Boltzmann Machine and Deep Belief Network are used to classify malware into families of Android application. A texture-fingerprint based approach is proposed to extract or detect the feature of malware content. A malware has a unique "image texture" in feature spatial relations. The method uses information on texture image extracted from malicious or benign code, which are mapped to uncompressed gray-scale according to the texture image-based approach. By studying and extracting the implicit features of the API call from a large number of training samples, we get the original dynamic activity features sets. In order to improve the accuracy of classification algorithm on the features selection, on the basis of which, it combines the implicit features of the texture image and API call in malicious code, to train Restricted Boltzmann Machine and Back Propagation. In an evaluation with different malware and benign samples, the experimental results suggest that the usability of this method---using Deep Belief Network to classify Android malware by their texture images and API calls, it detects more than 94% of the malware with few false alarms. Which is higher than shallow machine learning algorithm clearly.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.4
• /
• pp.343-348
• /
• 2014

Face recognition system has advanctage to automatically recognize a person without causing repulsion at deteciton process. However, the face recognition system has a drawback to show lower perfomance according to illumination variation unlike the other biometric systems using fingerprint and iris. Therefore, this paper proposed a robust face recogntion method against illumination varition by slective fusion technique using both visible and infrared faces based on fuzzy linear disciment analysis(fuzzy-LDA). In the first step, both the visible image and infrared image are divided into four bands using wavelet transform. In the second step, Euclidean distance is calculated at each subband. In the third step, recognition rate is determined at each subband using the Euclidean distance calculated in the second step. And then, weights are determined by considering the recognition rate of each band. Finally, a fusion face recognition is performed and robust recognition results are obtained.

• The Journal of the Korea Contents Association
• /
• v.12 no.12
• /
• pp.517-523
• /
• 2012

Biometrics is a study of identifying individual by using the features of human body. It has been studied for an alternative or complementary method for the classical method based on password, ID card, etc. In comparison with the fingerprint, iris, ear, palmprint, finger-knuckle print has been recently studied. This paper proposes an effective method for recognizing finger-knuckle print based on the feature of Gradient orientation. The main features of finger-knuckle print are the size and direction of winkles. In order to extract these features stably, we make a feature vector consisted of Gradient orientations after the preprocessing of enhancing non-uniform brightness and low contrast. Total 790 images acquired from 158 persons have been used at the experiment for evaluating the performance of the proposed method. The experimental results show the recognition rate of 99.69% and the relatively high decidability index of 1.882. These results demonstrate that the proposed method is effective in recognizing finger-knuckle print.

• The Journal of the Korea Contents Association
• /
• v.7 no.3
• /
• pp.1-8
• /
• 2007

The images, which were acquired from various systems such as CCTV and Robot, include many human faces. Because of a rapid increase in visual data, we cannot process these manually; rather we need to do these automatically. Furthermore, companies require automatic security systems to protect their new technology. There are various options available to us, including face recognition, iris recognition and fingerprint recognition. Face recognition is preferable since it does not require direct contact. However, the standard 2-Dimensional method is limited, so Morphable Models may be recommended as an alternative. The original morphable model, made by MPI, contains a large quantity of data such as texture and geometry data. This paper presents a Geometrix-based morphable model designed to reduce this data capacity.

• Advances in nano research
• /
• v.7 no.4
• /
• pp.233-240
• /
• 2019

The present research work reports in-vitro anti-cancer activity of biologically synthesized ZnO nanoparticles (ZnO NPs) against human carcinoma cells viz SCC-40, SK-MEL-2 and SCC-29B using Sulforhodamine-B (SRB) Assay. ZnO NPs were synthesized by a unique and novel biological route using Temperature-gradient phenomenon where the extract of combination of Catharanthus roseus (L.) G. Don (C. roseus), Azadirachta indica (A. indica), Ficus religiosa (F. religiosa) and NaOH solution were used as synthesis medium. The morphology of the ZnO NPs was characterized by Transmission Electron Microscopy (TEM). TEM images reveal that particle size of the samples reduces from 76 nm to 53 nm with the increase in reaction temperature and 68 nm to 38 nm with the increase in molar concentration of NaOH respectively. XRD study confirms the presence of elements and reduction in crystallite size with increase in reaction temperature and NaOH concentration. The diffraction peaks show broadening and a slight shift towards lower Bragg angle ($2{\theta}$) which represents the reduction in crystallite size as well as presence of uniform strain. The FTIR spectra of the extract show transmittance peak fingerprint of Zn-O bond and presence of bioactive molecules These NPs exhibit inhibition greater than 50% for SCC-40, SK-MEL-2 and SCC-29B cell lines and more than 50% cell kill for SCC-29B cells at concentrations < $80{\mu}g/ml$. Nanoparticles with smallest size have shown better anti-cancer activity and peculiar cell-selectivity. The combination of extracts of these plants with ZnO NPs can be used in targeted drug delivery as an effective anti-cancer agent, a potential application in cancer treatment.