The special problem entitled "Missing Persons and Wanted Fugitives Information and Reporting System Using Face Recognition for Cross-Matching" prepared and submitted by Alee Ciaral P. Policarpio in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science has been researched and set for approval. Accepted and approved as partial fulfillment of the requirements for the bachelor's degree in computer science.
Mathematical and Computer Sciences Unit Department of Physical Sciences Department of Physical Sciences and Mathematics. The Philippine National Police does not have a missing persons reporting system and also still relies on primitive ways of publishing the identities of missing and wanted persons. This study proposes an information system that would serve as a centralized database for missing persons cases.
The system will serve as online publication of missing person and wanted fugitive cases and will also allow the public to post tips about the cases. The system includes a face recognition module implemented using local binary patterns for case cross-matching, which is also a method of information retrieval using image.
Background of the Study
The report will be placed on the Police file and the case will be assigned to an officer who will work with you and keep you informed of any progress that has been made. remain your point of contact. phoneDirectory">Phone Directory. lt;!--custom script for the whole page-->. Source code 123: sidebar cr.jsp. lt;span>Type a case. lt ;span>View Entries< /span>. lt;span>Face Recognition. lt;span>Advanced Search. Source Code 124: general sidebar.jsp. lt;span>View Entries .lt;span> Face Recognizer.lt;span>Advanced Search.
Source code 125: sidebar po.jsp. lt;span>View records. lt;span>Face Recognition. lt;span>Advanced Search. Source code 126: sidebar sa.jsp. lt;span>User Accounts. lt;team>Create. Sys ad. lt;script src=’https://www.google.com/recaptcha/api.js’>.
I understand that providing false information may result in fines, imprisonment, or both. lt;p>Your tip has been submitted. Thanks for your cooperation.
.. lt;p>An error occurred during registration. Please try again or contact the system administrator.Source code 128: send tip.jsp. lt;!-- custom form validation script for this page -->. lt;!--custom script for all pages-->. -IRS | Welcome, ${loggedInUser.firstName }. lt;th>Date of registration. lt;!--custom script for all pages-->. userTable').pageMe({pagerSelector:'#userPager',showPrevNext: . true,hidePageNumbers:false,perPage:3});. -IRS | User accounts. lt;!--custom script for all pages-->. lt;title>MW.
-IRS | View all Missing. firstname} ${missing.middleName} ${missing.lastName}. lt;!--custom script for all pages-->. myTable').pageMe({pagerSelector:'#myPager',showPrevNext:true, hidePageNumbers:false,perPage:5});. Source code 135: view all tips.jsp. gt;Close. gt;Close. gt;Close. gt;Close. lt;!--custom script for all pages-->. -IRS | View all Wanted. lt;!--custom script for all pages-->. myTable').pageMe({pagerSelector:'#myPager',showPrevNext:true, hidePageNumbers:false,perPage:5});.
Statement of the Problem
Objectives of the Study
The study aims to create an Information and Reporting System for Missing and Fugitive Persons with the following functionalities:. a) view and search through the list of missing persons with the status of 'missing' and wanted persons with the status of 'wanted' by filling in the text fields. Perform face recognition using Local Binary Patterns (LBP) after presenting a query image. a) Perform face detection using the LBP method on the query image.
Significance of the Project
The facial recognition cross-matching capability of the system is also handy when identifying an eyewitness description of a suspected criminal through facial composites and artist's sketches. The system can register the face in the sketch and find entries in the database with the most significant similarities from the query image. The criminal registrar may still include records of released and apprehended criminals in the system, but these will no longer be available to anonymous users.
Such records can still be used as future reference and can be included in the cross-match using facial recognition. Updates in the database can be automatically reflected in the online website which can be accessed by anonymous users. The system allows the general public to search records of missing persons and wanted fugitives through text-based information and also by cross-matching through facial recognition.
MWIRS allows the user to send case tips electronically through the system and the tip would be immediately routed to the officer from the office where the case was reported. MWIRS is an information system that can be accessed by the general public and allows them to submit tips and is equipped with a cross-match function through text information and facial recognition, which allows information to be processed in an organized manner, while helping investigators to solve and get to the bottom of crimes and other incidents .
Scope and Limitations
Assumptions
Review of Related Literature 11
Given a test image, a face recognition system must find the closest test match in the database. Thus, public safety requires robust facial recognition that can identify individuals in uncontrolled systems [8]. Facial recognition plays an important role in surveillance imagery which is one of the goals of the FBI's Next Generation Identification Program [7].
Facial recognition systems return a match score between face images that indicates their level of similarity. Instead, investigators use facial recognition systems to identify sets of candidates, and from there, additional clues and information can be used to fully identify a case [7]. 14] proposed a new feature extraction technique built on HT to be used for face recognition called Block-wise Hough Transform Peaks (BHTP) method.
The triangulation of these points allows the reconstruction of a simplified 3D face geometry, which is used for face recognition. These modules include libraries dedicated to face detection in photos and videos and multi-method face recognition.
Missing Person
Wanted Fugitive
Tip
In forensics, facial recognition technology, along with fingerprint and DNA identification, is necessary for continued progress in improving the range of tools available to determine a person's identity. Standard automatic facial recognition completely performs the identification of a subject, while forensic facial recognition only helps investigators narrow down a subject's identity. Eigenfaces and PCA were used by Sirovich and Kirby to efficiently represent the face, after which Turk and Pentland applied the Eigenfaces to solve recognition problems.
It has been used for texture description for more than a decade and has recently been successfully applied to facial expression analysis and facial recognition due to its low dimensionality and high efficiency [9]. The Local Binary Pattern Operator is one of the best performing descriptors for textures and is widely used in various applications. Mugshots include the majority of facial images used in forensics, but there are times when no photograph is available, resulting in a forensic sketch being generated.
eLBPH is used over hLBPH because standard texture analysis is not suitable for face recognition, and eLBPH is more appropriate, although it is relatively complex and sensitive [ 17 ]. Qasim el al [20] used OpenCV along with MATLAB to compare PCA and LBP methods for face recognition and their study showed that LBP outperformed PCA in terms of accuracy, but LBP took longer to recognize a face .
Artist’s Sketch
Mass Surveillance
Information System
A database is an organized collection of information, usually consisting of linked data files. Telecommunications enable the electronic transmission of information for communication, which enables information systems to perform processes and tasks via computer networks [28]. The four most common types of information systems are transaction processing systems, management information systems, decision support systems, and executive support systems.
Decision Support Systems manipulate and use the information from the MIS and/or TPS to generate insights and new information. Executive Support Systems organizes data and information from both MIS or TPS and external data sources [29].
Artificial Intelligence
Face Detection
Face recognition applications aim to determine the number of faces in an image and return its location in the image. There are four categories for knowledge-based face detection methods, feature-invariant approaches, template matching, and appearance-based. Knowledge-based methods use the relationship between facial features and are mainly designed for face localization.
Feature-invariant approaches aim to find structural features that exist even when pose or lighting conditions vary and are also used for face localization. Template matching methods use standard patterns of a face to describe the face as a whole or facial features separately. Appearance-based methods use a model from a set of training images that capture the representative variation of facial appearance and are designed for face recognition [32].
Face Recognition
Local Binary Pattern
OpenCV
Design and Implementation 31
The context diagram for the MWIRS has 4 external entities - anonymous user, Crime Registrar, Police Officer and System Administrator. An anonymous user can submit account information to the system and register an account and view existing cases of missing persons with 'missing' status and wanted fugitives with 'wanted' status. A crime registrar can log into the system by providing login details, create and update missing person and wanted fugitive records, manage his/her own account and view all missing person and wanted fugitive cases.
A police officer can log into the system by providing login details, manage his/her own account and view all cases of missing persons and wanted fugitives. A system administrator can log into the system by providing login details, creating another system administrator and managing all user accounts.
Use Cases
Entity-Relationship Model
Data Dictionary
Technical Architecture
System Architecture
Results 43
Java Files
JSP Files
Javascript Files
CSS Files
