This thesis proposes using face recognition algorithms to manage a photograph database by extracting faces from images, classifying them, and indexing them. The indexed values would then be used to logically organize the images in a database and enable searching for related images based on faces. Principal component analysis is used to extract features from each face, and a neural network is used for classification. The system aims to address the challenges of locating specific photos from large personal collections by automatically tagging photos with detected faces that can then be searched.

1. Photograph Database
management
using face recognition
By:
Amrit Ranjan

2. Abstract
This thesis proposed the face recognition method using common and most sophisticated face recognition
algorithm to maintain and manage image or photograph database. Here Photograph Image means Image
with human faces. In this thesis, image’s faces are extracted and classified and indexed. Indexed values
are later used for creating logical database of images. This indexed values will be used to search and
display related images. This is also features about the usage of the indexed values to identify or search
one face with combinations of other faces and it will help police to investigate in more details. In this
thesis a feature is extracted using principal component analysis and then classification by creation
neural network. Recently, the PCA (Principal Component Analysis) has been extensively employed for
face recognition algorithms. It is one of the most popular representation methods for a face image. It
not only reduces the dimensionality of the image, but also retains some of the variations in the image
data. We run our algorithm for face recognition application using principal component analysis. The
system produces promising results for face verification and face recognition. Demonstrate the
recognition accuracy for given number of input pattern. Our approach treats face recognition problem as
intrinsically(inherent) two-dimensional (2-D) recognition problem rather than requiring recovery of
three-dimensional(3-D) geometry, taking advantage of fact that faces are normally upright and thus may
be described by a small set of 2-D characteristic views. The system functions by projecting face images
onto a feature space that spans the significant variations among known face images. The significant
features are known as “eigenfaces”, because they are the eigenvectors (principal components) of the
set of faces. Computer model of face recognition in particular, are interesting because they can
contribute not only to theoretical insights but also to the practical applications. Computer that
recognizes faces could be applied to a wide variety of problems like criminal identification, security
system, image and film processing and human-computer interaction.

3. Introduction
 We are living in Digital world with easy accessibility of Digital camera Phone
Tablet etc. On average we click minimum 10-20 photographs per week which
sum-up 700-800 photographs per year.
 It is now very difficult to locate specific photograph (e.g. photograph with my
mother). One way to handle the situation to keep photo in different
directories with proper tagging. But it leads to duplicating same photographs.
 This thesis work is carried out to feasible study to address the issues
identified (as above) and corresponding implantation using some available
framework (EMGU).
 This solution indexes each photograph and faces. User can search on basis of
Face name (with combinations like Photograph with My Face + Mother’s Face)

4. Problem Statement
 In Digital world managing bulk of photographs with proper face index.
 Search photographs with face names.

5. Objective
 Set proper listener to the directory where photographs will be stored.
 Index each photograph with face name using face detection algorithm.
 Indexing should happen as soon as photographs will copied to designated
directory.
 Provide search mechanism to search photographs with combinations.

6. Methodology
 Face RecognitionDetection
 Face Indexing
 XML Based Indexing solution
 Face Search

7. System Configuration
User System Setting Database
Is First Time
Configuration Page
Yes
Image Directory Settings Saved

8. System Configuration

9. System Configuration

10. System Configuration

11. Face RecognitionDetection
User System Physical Storage Logical Storage
Set Listener
Copy Photo
Notify Image Added
Detect Faces
Notify user to Name
face
Map faces
Index Image with face name

12. Face RecognitionDetection

13. Face DetectionRecognition

14. Face Search
User System Logical Storage Physical Storage
Search Request
Search UI
Show
Search Faces
Image details
Load Image
Notify User

15. Face Search

16. Face Search

17. Face Search