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UDP - Project Report

On

Data Protection Using Hand Gesture

By

Nikhil Marathe (131000107007)

Guided By

Mr.Maulik Chaudhari

Assistant Professor at CE Department,

Sigma Engineering College, Matar

A Project Report Submitted to

Gujarat Technological University

In Partial Fulfilment of the Requirements for the

 Degree of Bachelor of Engineering in

 Computer Engineering

Department of Computer Engineering

Sigma Engineering College

Matar - 392035, Gujarat-India

December -2016

Chapter No. Topic Name Page No.

1 Certificate 2

2 Compliance Certificate 3

3 Gtu Certificate 4

4 Plagiarism Certificate 5

5 Acknowledgement 7

6 Abstract 8

Chapter : 1 Introduction

1.1 Introduction 1

1.2 Aim & objectives of project 7

1.4 Brief literature review & PAS 8

1.5 Plan of project work 23

1.6 Software & Hardware Required 24

Chapter : 2 DESIGN

2.1 Canvas 26

Chapter:3 Implementation

3.1.1 Screenshots

3.1.2 Security 34

3.1.3 Requirements 34

3.1.4 Advantage 34

Chapter:4 Summary

4.1 Conclusion 36

4.2 Scope of future work 36

4.3 References 37

INDEX

CERTIFICATE

This is to certify that Nikhil Satish Marathe(131000107007), of class B.E. Computer Engineering (7th Semester) at Sigma Engineering College, Matar has been satisfactorily completed their project work on “DATA PROTECTION USING HAND GESTURE\" for the term ending in December 2016.

Date:

Place: Matar

Asst.Prof.Maulik Chaudhari Prof. AnkitDarji

Comp. Engg. Dept. Head of Department,

S.E.C., Matar. Comp. Engg. Dept.,

S.E.C., Matar.

Seal

Sigma Engineering College, Matar.

.Examiner(s): ------------------------------

COMPLIANCE CERTIFICATE

This is to certify that IDP/UDP project work entitled “DATA PROTECTION USING HAND GESTURE” was carried out by Nikhil Satish Marathe (131000107007) at Sigma Engineering College, Matar (100). They have compiled to the comments given by the Internal Reviewer to my satisfaction.

We hereby certify that we are the sole authors of this UDP project report and that neither any part of this IDP/UDP project report nor the whole of the UDP Project report has been submitted for a degree by other student(s) to any other University or Institution.

We certify that, to the best of our knowledge, the current UDP Project report does not infringe upon anyone’s copyright nor violate any proprietary rights and that any ideas, techniques, quotations or any other material from the work of other people included in our UDP Project report, published or otherwise, are fully acknowledged in accordance with the standard referencing practices.

Date:

Place: Matar.

Team Guide

Nikhil Satish Marathe (131000107007) Asst.Prof.Maulik Chaudhari

Comp.  Engg.  Dept.,

SEC,  Matar.

Acknowledgment

We would like to acknowledge the contribution of certain distinguished people, without their support and guidance this project work would not have been completed.

We take this opportunity to express our sincere thanks and deep sense of gratitude to my project guide Mr. MAULIK CHAUDHARI, Assistant Professor of Computer Engineering in Sigma Engineering College, for his guidance and moral support during the course of preparation of this project report.  

We take this opportunity to thank all our friends and colleagues who started me out on the topic and provided extremely useful review feedback and for their all-time support and help in each and every aspect of the course of my project preparation. We are grateful to our Sigma Engineering College for providing me all required stuff and good working environment.

We would also like to thank GTU for giving us such an opportunity to use our theoretical knowledge to develop a practical and real-life application. We are exposed to industrial environment through this project. While developing project, we also got a chance to learn time management and team –work.

At the end, we thank everyone who has helped and supported us during entire development process of Data Protection Using Hand Gesture.   

Data Protection Using Hand Gesture

Submitted By

Nikhil Marathe

Supervised By

Mr.Maulik Chaudhari

Asst.Prof. Comp.  Engg.  Dept.

SEC,  Matar.

ABSTRACT

Now-a-days there is a problem that our confidential data got easily access by the unauthorized user by hacking the person password ,so to more secure to our confidential data we will develop a system to protect data by an hand gesture of an authorized user. This system will give more protection or prevention to our data therefore the person will be stress free for his confidential data. Our system will only give access the confidential data by an authorized person. In this the hand gesture is particular stored in database and after that the authorized person makes the hand gesture &if that matches with the gesture stored in database then only it can access it.

It is a technique used by human to communicate and interact with machine naturally without any mechanical devices. Gesture recognition allows the computer to understand and bring the human ideas. Gesture recognition act as a bridge between machines and humans, which still limit the majority of input tokeyboard and mouse.. Hand gestures recognition provides a separate complementarymodality to bring ones ideas. Hand gesture is a method of non-verbal communication for humanbeings for its free hand expressions much more other than other parts. Hand gesture recognition has greaterefficient for human computer interaction system.

CHAPTER – 1

INTRODUCTION

1.1 Theory of Background

This project deals with the Data Protection Using Hand Gesture. This project is very helpful toas company chairmen & high profile individual person.

The growing quality demand in the Engineering sector makes it necessary to exploit the whole potential of stored data efficiently but give more security or prevention to the storage data facility as it is confidential data which cannot be exploit.

In this sense, now-a-days there will be attackers in numerous number who is hacking our account and take all our confidential data of a person. So, to free from attacker and protect our data we used this data protection using hand gesture system as it will provide access to our data by matching with the patterns stored in database

So due to this the attacker get problematic to access the data which is confidential and because of this our data is secured.

• HAND GESTURE RECOGNITIONAPPROACHES

1. DATA GLOVE BASED APPROACH

Data Glove based approach make use of glove-typedevice which could detect hand position, movementand finger bending. In this approach user require towear a glove like device, which act as sensors thatcan sense the movements of hand(s) and fingers andpass the information to the computer. This approachcan easily provides exact coordinates the location ofpalm and finger’s, and hand configurations. The mainadvantage of data glove based approach is high

accuracy and fast reaction speed but this approachcan be quite expensive.

2. COLOR GLOVE BASED APPROACH

Color glove based approach represent aagreementbetween data glove based approach and vision basedapproach. Marked gloves or coloured markers aregloves that worn by the human hand with somecolors to direct the process of tracking the hand andlocating the palm and fingers. It can provide theability to extract geometric features necessary toform shape of hand. The disadvantages are similar todata glove based approaches.

3. VISION BASED APPROACH

In vision based approach user need not require towear anything. Instead the system requires camera(s),which are used to capture the images of hands forinteraction between human and computers. Visionbased approach is simple. In vision based handgesture recognition system there is no need to wear

anything, this technology use a bare hand to extractdata for recognition. With the help of vision basedtechnology user can directly interact with the systemIn vision based hand gesture recognition system, thehand movement is recorded by videocamera(s).Vision based technology deals with someimage characteristics such as texture and color foracquiring data needed for gesture analyze.

 Types are as follows,

(i) 3D hand model based approach

(ii) Appearance based approach

a. 3D MODEL BASED APPROACH

Three dimensional hand model based approachrepresent the 3D kinematic hand model and it try toestimate the hand parameters by comparison betweenthe input images and the possible 2D appearanceprojected by the 3D hand model. This approach isidea for realistic interactions in virtual environments.In contrast, 3D model based approaches can get thedepth information and are much morecomputationally expensive but can identify handgestures more effectively. 3D Model can be dividedinto volumetric and skeletal models. Volumetricmodels is the 3D visual appearance of human handand usually used in real time applications. The mainproblem in 3D model based technique is that it dealswith all the parameters of the hand which are hugedimensionality. Skeletal models in which it overcomevolumetric hand parameters problem by limiting theset of parameters to model the hand shape from 3Dstructure.

b. APPEARANCE BASED APPROACH

Appearance based approaches is also called as ViewBased. Approach, which model the hand using theintensity of 2D images and define the gestures as asequence of views. These models don’t use a spatialrepresentation of the body, because they derive theparameters directly from the images or videos using atemplate database. Some model are based on thedeformable 2D templates of the hands. Appearancebased approaches considered easier than 3D modelapproach, due to the easier extraction of features in2D image.

• APPLICATION

 Sign language recognition

 Robot control

 Graphic editor control

 Virtual environments

 Number recognition

 Television control

 3d modeling

1.2 Aims & Objective

1.2.1Aims:-

 To provide security to our confidential data & preventing from attacker manipulation.

1.2.2Objectiive:-

 Free from attacker manipulation

 Secured our confidential data

1.3problems specification

 Sensor not working properly

 Database connectivity

 Camera not working properly

1.4Brief literature review & PAS.

 RESEARCH PAPER 1:

Research Name:

Human Computer Interaction using Hand Gesture

Abstract: Hand gesture is a very natural form of humaninteraction and can be used effectively in human computer interaction (HCI). This project involves the design and implementation of a HCI using a small hand-worn wireless

module with a 3-axis accelerometer as the motion sensor. Thesmall stand-alone unit contains an accelerometer and a wirelessZigbee transceiver with microcontroller. To minimizeintrusiveness to the user, the module is designed to be small(3cm by 4 cm). A time-delay neural network algorithm isdeveloped to analyze the time series data from the 3-axisaccelerometer. Power consumption is reduced by the non-continuoustransmission of data and the use of low-powercomponents, efficient algorithm and sleep mode betweensampling for the wireless module. A home control interfaceisdesigned so that the user can control home appliances bymoving through menus. The results demonstrate the feasibilityof controlling home appliances using hand gestures and wouldpresent an opportunity for a section of the aging populationand disabled people to lead a more independent life.

Advantage :  Help the aged people.

 Easy to use

Conclusion: This project demonstrated the feasibility of designing and

implementing hand gesture recognition devices using a

three-axis accelerometer, a small wireless transceiver

module as well as implementing an embedded neural

network in the device to make it standalone. The Home

Control Interface also demonstrates the feasibility of controlhome appliances using the hand gesture, and would presentan opportunity for a section of the aging population anddisabled people to lead a more independent life.

Research Paper 2

                    Research Name: HAND GESTURE RECOGNITION SYSTEM USING IMAGE PROCESSING

Abstract: Image processing has a very big potential to do virtually anything. But in real life,worse come to worst when the development of particular interest is not being done

properly. This project comes to the extent of development details on recognition systemby using state-of-the-art NI LabVIEW graphical programming software. The

complexness and configurable in so many way of today’s entertainment has brought usback to basic of safety. It is worthless to have a complete system that can do almost

anything but compromises human life. To cope up on par to today technologicalachievement, this project will try to bring sophisticated ways of using image processing

as a solution to deliver command in the other way. The hardware is being interfaced byusing Software Development Kit (SDK) from the supplier of the hardware, in this case isLogitech Inc. Proper data channeling between hardware and software ensure smooth

transaction that increase performance and capability. The method of backlighting is usedto give proper exposure to the subject so that the further processing and blob (binary

large object) analysis can be done on it. This system also used algorithm of severalprocessing technique that may or may not be the same output for each type of it. The

system is upgradeable to be connected by separate module. It will not be viable toimplement it today, but the ever falling prices of gadget plus a little bit of innovation into

infrared lighting, 0 lux night vision acquisition, refine image processing and fuzzy logicto keep the system trained, it will be everyday must.

Advantage :  You  can remove unwanted objects.

 Easily recognization is done.

Disadvantage :  It only works on image.

 Time consuming

Conclusion :

As early as in 1670, there’s an expertise for human eyes named optometrist tohelp its patient to have a better vision on their surrounding. The first one is Benjamin

Franklin that invented the first pair of bifocal glasses [1]. Benjamin’s intention is toimprove visibility and at that time not to aid people with sight problem like most people

today. That context is referring to human capability of seeing things, contributing to avery highly valuable gift. Thanks to the fine creation of god, we do have two eyes that isone of tool to predict and act verily according to the vision tells and guides.Just imagine how this world is if we are normal human being with healthy eyes,

then we lost the vision or capability of capturing images and color. Even with one eyes,we have difficulties of estimate the distance of an object. Then, we immediately lostcoordination and physical sense of everything around us. This situation best describe byhaving woman protect herself from strangers just by spraying chili aerosol to paralyze itsattacker vision for a moment.

Research Paper 3

                    Research Name:

Study on Various Techniques in Hand Gesture

Recognition

Abstract: Hand Gesture recognition is a techniqueused by human to communicate and interact withmachine naturally without any mechanical devices.Gesture recognition allows the computer tounderstand and bring the human ideas. Gesturerecognition act as a bridge between machines and

humans, which still limit the majority of input to

keyboard and mouse. Gesture recognition in which it

recognize the expressions of motion by a human such

as hands, arms, face, head, and body. Hand gestures

recognition provides a separate complementary

modality to bring ones ideas. Hand gesture is a

method of non-verbal communication for human

beings for its free hand expressions much more other

than other parts. Hand gesture recognition has greater

efficient for human computer interaction system.

Advantage :  Good performance system with the complex background

 Sufficient reliable for recognition systems.

Disadvantage :  Irrelevant object might overlap with the hand

 Wrong object extraction appeared if the object

larger than the hand.

Conclusion :

In this survey paper, compare to Data glove based

approaches, Color glove based approaches, Vision

based approaches, Appearance based approaches, 3D Model Based Approaches, Contour based model.

Contour based model is more accurate. In contour

based model per-class accuracy for pixels located on

the hand contour and the per-class accuracy by using

the contour model. Compared with the results

provided by the pixel classification, there is a large

improvement in contour model based classification.

The average accuracy of hand parts classification is

improved.

Research Paper 4

Research Name:

AUTOMATIC STATIC HAND GESTURE RECOGNITION USING TOF CAMERAS

Abstract: This paper presents an automatic algorithm for static hand

gesture recognition relying on both depth and intensity

information provided by a time-of-flight (ToF) camera. Thecombined depth and intensity information facilitates thesegmentation process, even in the presence of a clutteredbackground (2 misses out of 450 images). Gestureclassification is based on a decision tree using structuraldescriptions of partitioned contour segments. Classificationwas tested on 9 different gestures. The final meanrecognition rate is satisfactory, of about 93.3%.

Advantage :  Simple,fast easy to implement

 Apllied on real system

Disadvantage :  System limitation restrict the application

Conclusion :

An automatic method for static hand gesture recognition

using a ToF camera was presented. Hand segmentation is

straightforward using a region-constrained region growing

algorithm which considers both depth and intensity image

data. Gesture classification occurred with a decision tree

exploiting structural descriptions of partitioned segments.

The classification is in principal robust to contour

fragmentation and is translation invariant, which however

was not particularly exploited here. The original method

described in [11] offers to the classifier a very good

description of the contour structure which enables the

subsequent identification of the fingers. If more than 9

gesture classes were used, then the decision tree had to be

certainly more complex. However the recognition principledemonstrated here is certainly promising.

Research Paper 5

                    Research Name: Wireless Communication Glove Apparatus for Motion

Tracking, Gesture Recognition, Data Transmission, andReception in Extreme Environments

Abstract: Military personnel need better ways to communicate in hostile,noisy, silence-mandated, and/or extreme environments. Typing ona keyboard is difficult and impractical while wearingcomprehensive protective clothing. Wireless data gloves wereresearched and developed to transmit and receive ASCII code and

other signals as hand gestures. Two categories of glove prototypeswere constructed: gloves with and without a haptic-IO capability.All data gloves detect motion, such as gestures, using magneticsensors. Non-haptic gloves only transmit static and dynamicgestures. Haptic gloves have vibro-mechanical devices on thefingertips for feedback about transmitted signals and for covertsignal

reception. Many potential communications applications

include hazardous and covert military operations, space operations,fire fighting, mining, training, underwater use, and aids for thevisually and hearing impaired.

Advantage :  It could be applied on robot control

 No training is required

Disadvantage :  Performance recognition decrease when the distance is greater than 1.5 between the user and camera

Conclusion :

Military personnel need better ways to communicate in hostile, is especially true while wearing comprehensive protective clothing,such as Mission-Oriented Protective Posture (MOPP) gear or spacesuits. Even a simple task such as typing on a keyboard becomesunwieldy. This paper describes a novel method for data and gesture

communications called “data gloves.” These data gloves wereresearched and developed to transmit and receive ASCII code andother signals in the form of hand gestures.

1.4.1 Patent-1

   Title: ENCRYPTION AND DATA-PROTECTION FOR CONTENT ON PORTABLE MEDIUM

Patent Number: US 20050114689A1

Application Number : 10/945,542

Applicant : Microsoft Corporation

Place: Redmond,WA(US)

Description : A source generates a medium key (KM) and a media secret table including a plurality of entries, each entry including (KM) encrypted by a public key (PU-PD) of a plurality of devices, obtains the medium ID of a medium there from, generates a content key (KD) for a piece of content, encrypts the content with (KD) to result in (KD(content)), encrypts (KD) with (KM) to result in (KM(KD)), generates a package for the content including (KD(content)), (KM(KD)), the medium ID, and a signature based on at least the medium ID and verifiable with (KM), and copies the generated package and the media secret table to the medium. Thus, a device with the medium and a private key (PR-PD) corresponding to an entry of the media secret table can access and render the content.

1.4.2 Patent-2

Title DYNAMIC AND STATIC HAND GESTURE RECOGNITION THROUGH LOW-LEVEL IMAGE ANALYSIS

Patent Number: US5454043A

Application Number : US08099944

Applicant : Mitsubishi Electric Research Laboratories Inc

Place: Cambridge, MASS

Description : A low-level model-free dynamic and static hand gesture recognition system utilizes either a 1-D histogram of frequency of occurrence vs. spatial orientation angle for static gestures or a 2-D histogram of frequency of occurrence vs. space-time orientation for dynamic gestures. In each case the histogram constitutes the signature of the gesture which is used for gesture recognition. For moving gesture detection, a 3-D space-time orientation map is merged or converted into the 2-D space-time orientation histogram which graphs frequency of occurrence vs. both orientation and movement. It is against this representation or template that an incoming moving gesture is matched.

1.4.3 Patent-3

                   Title : Fraud prevention techniques

Patent Number: US 20100130172A1

Application Number : US12626066

Applicant : Ring Central Inc

Place: San Mateo, CA (US)

Description : System, apparatus, computer program products and methods for preventing fraud attacks (e.g., on a virtual PBX service provider) are disclosed. In some implementations, a set of fraud evaluation processes are performed, an overall fraud evaluation score is incremented as each of the set of fraud evaluation processes are performed and a step result is obtained. A user request (e.g., account activation) can be denied or accepted based on the overall fraud evaluation score. In some implementations, the set of fraud evaluation processes can include one or more of: an internal fraud evaluation process, a process for checking multiple trial accounts associated with a common account parameter, a process for geolocation verification of multiple account parameters, a process for device type verification for a contact phone number, a process for credit card verification, and a process for placing a contact number verification call

1.4.4 Patent-4

                  Title : Database security via data flow processing

Patent Number: US20110219035A1

Application Number : US12982795

Applicant : Crossbeam Systems Inc

Place: US

Description : An apparatus and method to distribute applications and services in and throughout a network and to secure the network includes the functionality of a switch with the ability to apply applications and services to received data according to respective subscriber profiles. Front-end processors, or Network Processor Modules (NPMs), receive and recognize data flows from subscribers, extract profile information for the respective subscribers, utilize flow scheduling techniques to forward the data to applications processors, or Flow Processor Modules (FPMs). The FPMs utilize resident applications to process data received from the NPMs. A Control Processor Module (CPM) facilitates applications processing and maintains connections to the NPMs, FPMs, local and remote storage devices, and a Management Server (MS) module that can monitor the health and maintenance of the various modules.

1.4.5 Patent-5

                   Title : Encryption based on touch gesture

Patent Number: US9165159B1

Application Number : US14152863

Applicant : Marvell International Ltd

Place: Hamilton (BM)

Description : Some of the embodiments of the present disclosure provide a method comprising receiving an input from a touch input device. The input corresponds to a gesture produced by a user swiping a pattern on a surface of the touch input device. The method further comprises decomposing the gesture into segments, using a look-up table to determine alphanumeric elements that correspond to each of the segments, and assembling the alphanumeric elements into an encryption password.

1.5 Plan of project work

Activity JUL AUG SEP OCT

NOV

DEC

Problem Summary

Feasibility Analysis

Requirement Determination

Requirement Analysis

Requirement Specification

Documentation

1.6Software & Hardware Required

SOFTWARE:-

 ArcSoft

 Net Beans

HARDWARE:-

 Quick Cam Pro 5000

 Celeron processor

 256MB of RAM

CHAPTER – 2

DESIGN

2.1 CANVAS

2.1.1.AEIOU SUMMARY

Fig:-2.1.1

 Activities:-

In this process there are various activity are present such as:-

a) Enter password

b) Enter mobile number

c) Enter email id

d) Enter username

e) Verification code

 Environment :-

In this it provide us the scenario of the system like:-

a) Database problem

b) Attacker problem

c) Data security problem

d) Sensor problem

e) Connectivity problem

 Interaction:-

In this case it display who is interacting with whom like:-

a) Camera with database

b) User with camera

c) Sensor with camera

d) Camera with system

 Objects:-

It shows which are the object is present such as:-

a) Systems

b) Connectivity

c) Camera

d) Database

e) Pc

f) User

g) Sensor

 Users:-

In this case it shows us the user who can access to the system

a) Hardware developer

b) Customer

2.1.2. Empathy mapping canvas

Fig:-2.1.2

 User:-

a) Hardware developer

b) Customer

 Stakeholders

a) Hardware developer

b) Technian

c) Organization

d) Government authority

 Activities:-

a) Hand recognization

b) Enter password

c) Sensor sensing

d) Enter email id

e) Camera capturing

f) Enter mobile no.

g) Hand recognization matching with database

2.1.3. Ideation canvas:-

Fig:-2.1.3

 People:-

In this it include the involving of different person llike:-

a) Hardware developer

b) Organization

c) Customer

d) Technian

e) Government authority

 Activities:-

It include the various types of activites related to our system such as:-

a) To provide security

b) Gesture mapping with database stored gesture

c) Sensor sensing system

d) Camera recognization of hand gesture

 Situation/context/location:-

It involve the situation occurring for our system, also based on our context and finally it also depend on location for the system.

a) Sensor not working

b) Database connectivity

c) Camera not working

d) Hiding security attacker manipulation

e) Military application

f) company

2.1.4. Product Development:-

 Purpose:-

It provide us for what purpose we are making our project:-

a) to provide more security

b) to free from attacker manipulation

 people:-

It includes the number of people belonging to our system:-

a) Hardware Developer

b) Customer

 product experience:-

It state that what will be the experience of our system:-

a) it is easy to access our data

b) it provide security to data

 product function:-

It includes the what are the project function for our system:-

a) attacker manipulation

b) highly security

 product feature:-

It include what are the features in our system:-

a) camera recognization of hand gesture

b) secured data ass only access by authorized person

c) sensor technology

 components:-

It include what are the components required in our systems:-

a) sensor

b) pc

c) camera

d) Netbeans

e) MSVisio

f) My Sql

 customer revalidation:-

It gives the feedback for our project:-

a) movements of angle changes every time

b) backup of protection data should be there

 reject,redesign,retain:-

a) block of pixels should be display

b) eyes retina capturing or password should be there.

2.1.5:-BMC CANVAS:-

• Key Partners

1. Users

2. Web Service Provider\\Manager

  It is the network of suppliers and partners that make my model works.

• Key Activities

1. Provide Security

2. Gesture Movement

3. Camera Capturing Gesture

These are the main activities that make my model work

• Key Resources

1. Computer/Laptop

2. Internet

3. Web Camera

These are main resources, by the help of which my system is able to work on it.

• Value Proposition

1. Highly Secure Data

2. Quick &Efficient services

3. Easy to use

4. Platform independent

It is the clear description which increased the value of my systems for the customer.

• Customer Relationship

1. Self-services

2. Automated

It provide us the description about the relationship with the customer.

• Channels

1. Online Mode

It act as a mode for reaching to its destination and provide service to them.

• Cost Structure

1. Web Hosting

2. Developer

3. Web Camera

It describe whatever cost required to make our systems.

• Revenue Streams

1. Usage Fees

It is the generating and collecting income mechanisms.

• Customer Segments

1. General People

It is the people who all are attached with our systems.

CHAPTER – 3

IMPLEMENTATION

3.1.1.Screenshots

1.Homepage:-

2.Login Page:-

3.Password Recovery:-

3.Registration Page:-

3.1.4. Security:-

 Security is of main purposed while carrying out this Data protection using hand gesture. This system has being implemented proper security measures such as creating secure space between customer and attacker, due to which attacker cannot attack in our systems.

Proper access rights control is been implemented, So the system will provide the secure

Environment to each user and admin with the systems.

3.1.5. Requirement:-

 Whenever we does the movement of our hand for gesturing then the angle will be the different at each time so we have to do to make a block of pixels so it prevent to change the angle of our movement.

 In case of any failure in the hardware or sometimes we got the injury in our hand and due to this it cannot detect our hand properly so in that case there should be bacup password should be provided.

3.1.6. Advantage:-

 It  provide highly security

 It is easy to access our data

 It prevents from attacker

 It is also use for hiding our confidential data

CHAPTER – 4

SUMMARY

4.1   Conclusion

The growing quality demand for security of our data is very necessary in this world. The data is not only our personal information but it also include data which is more personal or confidential which can be access only to our authorized person.

In this sense, it gives more benefits as per the security purpose of our data and also gives free from the attacker manipulation.

4.2 Scope of future work

 It  provide highly security

 It prevents from attacker

 It is also use for hiding our confidential data

4.3 References

[1].Oprisescu, Serban, ChristophRasche, and Bochao Su. \"Automatic static hand gesture          recognition using tof cameras.\" Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European.IEEE, 2012.

[2].Pu, Qifan, et al. \"Whole-home gesture recognition using wireless signals.\"Proceedings of the 19th annual international conference on Mobile computing &networking.ACM, 2013.

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