ABSTRACT
Android Based Moving objects systems
are becoming increasingly important for crime investigation and the number of
cameras installed in public space is increasing. However, many cameras
installed at fixed positions are required to observe a wide and complex area.
In order to efficiently observe such a wide area at lower cost, mobile robots
are an attractive option.
This paper presents architecture to
improve surveillance applications based on the usage of the service oriented
paradigm, with android smart phones as user terminals, allowing application
dynamic composition and increasing the flexibility of the system.
According to the result of moving
object detection research on video sequences, the movement of the people is
tracked using video surveillance. The moving object is identified using the
image subtraction method. The background image is subtracted from the
foreground image. From that the moving object is derived.
So the frame algorithm and the
threshold value is calculated to find the moving image. Using frame algorithm
the moving frame is identified. Then by the threshold value the movement of the
frame is identified and tracked. Hence the movement of the object is identified
accurately.
OBJECT OF PROJECT
The ability to
extract moving objects in real time from live video data using an embedded
processor is our primary aim. Alert Sound.
PROBLEM DEFINITION
The
detection, matching and classification of human appearance is a challenging
problem. A further weakness of video detection is the limitation of
conventional camera systems to operate under wide dynamic range lighting, which
is typical for outdoor applications. Therefore, real-time video based tracking
application are mostly constrained with limited.
Disadvantage
Most of the
recorded images are of insufficient quality to hold as evidence in a law court
It is also expensive to have
human operators monitoring real-time camera footage 24/7.
EXISTING
SYSTEM
In the
existing system, the moving object is identified using the some algorithms
which are not exactly doing that detection works.
Image
is can be stored in the server and it can be retrieve after some time.
Moreover
there is no alert system to inform the admin when unknown object is detected.
Image
Retrieval from the remote place is not done in the existing system.
DISADVANTAGES
ü There is no accuracy in the captured image.
ü The moving object cannot be detected correctly.
ü No alert about the motion detection to the user.
ü Image cannot
be retrieve at the time of motion detection.
PROPOSED SYSTEM
Ø In the Proposed system, the moving object is
identified using the image subtraction method.
Ø The background image is subtracted from the
foreground image. From that the moving object is identified. Here we can detect
the exact image of the moving object.
Ø Another advantage of this system is when an unknown
image is captured by the system it will alert the user automatically by sending
an SMS to user’s mobile.
Ø User will be using Android Mobile for the Retrieval
of Images from the remote place to know whether those images are important and
can be ignored.
Ø If some known people would have entered in the
closed room, which can be ignored, as they are reliable people. In this paper,
we present a QoS-aware service-based architecture for surveillance systems, and
a prototype of this architecture, where a Android Based Moving objects application
is developed over the Android platform.
ADVANTAGES
High accuracy in image capturing
Send an alert to user’s mobile whenever a new object
is detected
Image can be stored in the server and can be view at
the time of motion detection
User can view the image, or video clips via his
Android mobile itself
Programming paradigms have allowed increasing the
dynamism and flexibility of distributed environments
SYSTEM SPECIFICATION
Software Requirements:
Ø Operating
system : Windows XP
Ø Technology
Used : Android 2.2
Ø IDE : Eclipse 3.4 (min)
Ø Emulators : Micro emulator 5055
Ø Plug-in : ADT plug-in
Ø Tools used : Android SDK1.2,
GoogleAPIv8 or minv7
Hardware Requirements
Ø Processor : Pentium P4
Ø Motherboard : Genuine
Intel
Ø RAM : Min
1 GB
Ø Hard Disk : 80 GB
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