Study of Cluster-Footprint Analysis Testing Algorithm and System

Yan Li; Nan Pan; Xing Wu; Chang Liu; Yi Liu

doi:10.4028/www.scientific.net/AMM.538.516

Paper Titles

Input-to-State Stability of Multi-Agent Systems
p.486

A Novel Multi-Service Passive Optical Network Based on the Wavelength-Division-Multiplexed Technology
p.490

Design of Intelligent Transportation Wireless Module Based on STM32F207
p.494

Research on the Applications and Characteristics of the Wireless Sensor Network
p.498

A Range Free Acoustic Localization Algorithm in Wireless Sensor Networks
p.502

The Study and Application of Improved Micro-Genetic Algorithm Based on Cauchy Mutation
p.508

An Improved Task Scheduling Algorithm Based on Multi-QoS in Cloud Computing
p.512

Study of Cluster-Footprint Analysis Testing Algorithm and System
p.516

Study of Intelligent Evidence Management System
p.520

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 538Study of Cluster-Footprint Analysis Testing...

Study of Cluster-Footprint Analysis Testing Algorithm and System

Abstract:

The cluster-footprint left at a crime scene is one of the most common trace evidence in the field of criminal investigation. Through analyzing and calculating the plane footprint, the investigators can get some important feature information such as step size, age and height, etc. However, this way is difficult to apply to reality without any errors in the process of manual calculations. Information management is more complicated in the later, the efficiency is relatively low too. To solve above problems, a testing system is designed and developed to analyze cluster-footprint. This system is based on the LabVIEW platform, which can realize image acquisition, stride characteristics extraction, information management and so on. Actual analysis results show that this system can effectively achieve these functions, working accuracy and efficiency can meet requirements of criminal investigation process.