Digital Image Processing

N. Kannaiya Raja ¹, K. Arulanandam ², R. Radha Krishnan ³, M. Nataraj ⁴

Affiliations
1 Department of CSE, Arulmigu Meenakshi Amman College of Engg., Thiruvannamalai Dt., Near Kanchipuram, IN
2 Department of CSE, Ganadipathy Tulsi's Jain Engineering College, Vellore, IN
3 Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya University, IN
4 Department of Computer Science and Engineering, Anna University, IN

Abstract

In this research, we consider the problems of registering multiple video sequences dynamic scenes which are not limited non rigid objects such as fireworks, blasting, high speed car moving taken from different vantage points. In this paper we propose a simple algorithm we can create different frames on particular videos moving for matching such complex scenes. Our algorithm does not require the cameras to be synchronized, and is not based on frame-by-frame or volume-by-volume registration. Instead, we model each video as the output of a linear dynamical system and transform the task of registering the video sequences to that of registering the parameters of the corresponding dynamical models. In this paper we use of a joint frame together to form distinct frame concurrently. The joint identification and the Jordan canonical form are not only applicable to the case of registering video sequences, but also to the entire genre of algorithms based on the dynamic texture model. We have also shown that out of all the possible choices for the method of identification and canonical form, the JID using JCF performs the best.

Keywords

Dynamic Textures, Video Registration, Nonrigid Dynamical Scenes.

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N. Kannaiya Raja ¹, K. Arulanandam ², R. Somasundaram ³

Affiliations
1 CSE Department, Arulmigu Meenakshi Amman College of Engineering, Thiruvannamalai Dt, Near Kanchipuram, IN
2 CSE Department, Ganadipathy Tulsi's Jain Engineering College, Vellore, IN
3 Arulmigu Meenakshi Amman College of Engineering, Thiruvannamalai Dt, Near Kanchipuram, IN

Abstract

Fingerprint system use in the pixel system for interacting to the problem of many fields. In this fingerprint system has generally represented by four schemes:grayscale image, phase image, skeleton image, and minutiae scheme which are used in this paper to find out spurious minutiae in the fingerprint. Most of the fingerprint reconstruction schemes has been existed which based on converting minutiae representation to phase (continuous phase and spiral phase). But this still contain a few spurious minutiae especially in high curvature region. For a direct use of the existing reconstruction algorithm to a latent fingerprint in NIST SD27. Both the ridge flow and minutiae in the reconstructed fingerprint match the original fingerprint well. But, apparently, the reconstructed ridge pattern does not match the original ridge skeleton exactly. This novel reconstruction method proposed the difficult and important problem of latent fingerprint restoration using significantly modified existing reconstruction algorithm to make the reconstructed fingerprints appear visually more realistic, brightness, ridge thickness, pores, and noise should be modeled. The accept rate of the reconstructed fingerprints can be further enhance by reducing the image quality around the spurious minutiae in the grayscale image and other features (such as ridge orientation and skeleton) manually marked by the latent expert.

Keywords

Reconstruction, Enhancement, Minutiae, Ridge Matching, Curve Matching.

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N. Kannaiya Raja ¹, K. Arulanandam ², G. Deepa ¹, M. Balaji ³

Affiliations
1 CSE Department, Arulmigu Meenakshi Amman College of Engineering, Thiruvannamalai Dt, Near Kanchipuram, IN
2 CSE Department, Ganadipathy Tulsi’s Jain Engineering College, Vellore, IN
3 Arulmigu Meenakshi Amman College of Engineering, Thiruvannamalai Dt, Near Kanchipuram, IN

Abstract

One way to protect organizations from malware is to deploy high-speed network based intrusion detection systems on the communication lines. This approach is achieved by P-DPL. Such appliances perform deep-packet inspection in real- time and use simple signatures for detecting and removing attacks such as malware, propagating worms, denial-of-service, or remote exploitation of vulnerabilities. P-DPL is primarily intended for high-speed network traffic filtering devices that are based on deep-packet inspection. Malicious executables are analyzed using two approaches: disassembly, utilizing IDA-Pro, and the application of a dedicated state machine in order to obtain the set of functions comprising the executables. The signature extraction process is based on a comparison with a common function repository. By eliminating functions appearing in the common function repository from the signature candidate list, P-DPL can minimize the risk of false-positive detection errors. To minimize false-positive rates even further, P-DPL proposes intelligent candidate selection using an entropy score to generate signatures.

Keywords

Automatic Signature Generation (ASG), Malware, Malware Filtering, Packet-Deployment Payload (P-DPL).

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