1. 2012 International Conference on Computer Science and Electronics Engineering
Image processing and detection based on
ARM+Linux platform
Zhang Xiaozhi
Department of information Engineering
Zibo vocational institute
Zibo,shandong,china,255314
zhangxiaozhi1116@126.com
Abstract—video monitoring system plays a vital role in
maintaining social stability, it can capture device and monitor the
scene by making use of camera and advanced image recognition GPRS
technology. When the abnormal situation is discovered, it can FLASH
USB
send out alarm sound and record the scene at the same time by
using pictures or video, and at last use a variety of ways to notice CAMERA
the danger. The topic on video monitoring system is one of the SDRAM
key parts -- image acquisition processing and detection, using the LCD
platform of Beijing BoChuang UP-NETARM2410-S ,this paper
introduce the image information processing as well as of the CPU
movement object detection.
Keywords- three frame difference algorithm; threshold; median
filtering method
Fig 1 Structure of the system
I. INTRODUCTION
The camera is mainly responsible for the collection of
As the video monitoring system developing more than 20 image information, the camera has used the mesh 2000B, it has
years, it experiences from analog to digital. The hardware and the advantages of fast speed, low power consumption
software are correspondingly improved in the functional and advantages. Its speed in the 352 * 288 resolution can be
performance, but many deficiencies still exist. The original reached at least 25FPS, and support 24 bit color depth, its
control is manual operation. Artificial monitoring system can image quality is very good, many parameters with it can be
consume quite a lot of manpower and material resources and adjusted by hand, brightness and exposure also can be adjusted
not be remotely controlled, and the function is also single, automatically. Mesh 2000B can use USB interface, connection
which will result to that the error report rate is high, it can only and convenient to use, does not require an external power
alarm on the spot and can not achieve real-time remote alarm to source.
reduce losses and the working situation of record. These
drawbacks make alarm system will fail to alarm and alarm After system acquire image by use of camera continuously,
error information, alarm system security and utility will it will process a series of image to get the final image, and
seriously reduce. judge by the image to decide whether to use the GSM network
alarm the user and display on the LCD [3].
The video monitoring system needs to monitor and detect
the work locations, according to the acquired image
information, so it is very important to process the image. This III. IMAGE PROCESSING
article will focus on the introduction of image acquisition and A large amount of noise maybe produced when receiving
moving image detection according to the collected images [1]. video frame for the influence of equipment. So de-noise
method of image median is needed first, and then the three
II. SYSTEM PLATFORM frames algorithm method, which are developed for board
camera is used to analyze the image [4], after that if there is the
This paper is based on the Beijing BoChuang S3C2410 moving object is judged according to the image.
embedded experiment platform. The experimental platform
adopted S3C2410 processor, the internal integrated ARM920T Image preprocessing of the system is image denoising,
processor for 32 bit MCU of the ARM Company, which has which is the first step after the original image extracted.
the advantages of small volume, high performance, low cost Image is denoised by the way of 3 * 3 median filter, and
and low power consumption, the frequency of it is up to system use rapid parallel median filter, which can avoid
203MHz. In addition, the platform is also equipped with 64M amount of the repeated comparison operation. Each window of
NAND FLASH and 64M SDRAM [2]. System structure m ), the whole time of
diagram is shown in Figure 1 system structure. the filter need time about O
978-0-7695-4647-6/12 $26.00 © 2012 IEEE 399
DOI 10.1109/ICCSEE.2012.245

2. 2
whether or not movement object by the difference of threshold
calculation is O ( N
*m
) ,and it’s easy to realize parallel of image.
processing on hardware processor. Its fast algorithm and
implementation is as follows: According to the experimental observation, the system gets
the way of judging movement objects by way of threshold: for
1) For illustration, each of the 3 x 3 pixels within the
window is respectively defined as follows and the pixels are three successive images
p i −1
(x, y) p i
(x, y)
arranged as shown in Table . p i +1
(x, y)
.
1. That whether d i − 1 , i or d i , i + 1
TABLE I. PIXEL ROWS LIST
( x, y) ( x, y)
is more than
zero column first column second column or equal to 20 shows existence of movement objects.
(x, y) −
2. When d i − 1 , i d i ,i + 1
zeroth line P00 P01 P02 | (x, y) |
is more than or
first line P10 P11 P12 equal to 10, it shows existence of movement objects.
second line P20 P21 P22 In the process of detecting of movement object, there may
2) First of all, each column (or row) within the window will be too fast or too slow movement objects which can’t be
be calculated to get the maximum value, median value and the detected only by three continuous frames. So the system
minimum value. By this way there will be three set of data, doesn’t just use three continuous image frames to carry out
which can be respectively marked for the maximum value operation but to detect movement objects by using “double
group, the median group and the minimum group. The frame three” method according to the characteristics of camera
calculation process is represented as follows: [7]. That is when the first" three frame" could not detect the
movement information, then the second" frame three" can be
MAX0=MAX(P00,P10,P20);MAX1=MAX(P01,P11,P21), used to detect it. If the second" frame three" can’t detect the
MAX2=MAX(P02,P12,P22) movement objects, we can use the value of the difference
MED0=MED(P00,P10,P20);MED1=MED(P01,P11,P21), image which come from the subtraction of continuous " frame
MED2=MED(P02,P12,P22) three". Then we can judge there is a movement object whether
or not and operate just like this again and again. Using this
MIN0=MIN(P00,P10,P20);MIN1=MIN(P01,P11,P21),MI method we can not only detect movement objects too fast but
N2=MIN(P02,P12,P22) also movement objects too slow. And the detection effect is
3) It can be seen that the maximum value of maximum very good. Movement object extraction processes such as
value group and the minimum value of minimum value group Figure 2 movement object extraction process chart.
must be the maximum and minimum value of the two columns Capture three frames of image(P1,P2,P3)
within the nine pixels. Minimum value of median group is less take the difference of image P2-P1 and
than five pixels at least. Similarly, the median value of P3-P2 and threshold T1 T2
maximum group is more than five pixels and the median value
in the minimum group is less than 5 pixels at least. We can note
the minimum value in maximum group of MAX_MIN, the T1>=20 || T2>=20 ||
Y
alarm
median value in median group of MED_MED and the T1-T2 >=10
maximum value in minimum group of MIN_MAX. then
WINMED which is output pixel value from filter results should N
be the median value of MAX_MIN, MED_MED and Capture three frames of image(P1ƍ,P2ƍ,P3ƍ)
MIN_MAX. The computational process is represented as take the difference of image P2ƍ-P1ƍ and
follows: P3ƍ-P2ƍ and threshold T1ƍ T2ƍ
WINMED = MED(MAX_MIN MED_MED MIN_MAX).
Using this method, the median is calculated for seventeen T1ƍ>=20 || T2ƍ>=20 ||
Y
times. Compared with the traditional algorithm, it can reduce T1ƍ-T2ƍ >=10
for in the number of nearly two times, and the algorithm is very
applicable to the real-time processor for parallel processing. N
T11ƍ= P1-P1ƍ T22ƍ= P2-P2ƍ
IV. MOVEMENT INFORMATION DETECTION T33ƍ= P3-P3ƍ
Movement information detection is mainly responsible for
difference value and threshold calculation coming from the
Y
acquired image frames. And then it can judge that there is T11ƍ>=15||T22>=15 ||
T33ƍ>=15
whether or not movement objects [5] [6]. The development of
three frames algorithm method is used for image processing. N
This method can observe the threshold under the condition of
existing movement objects and static objects and then identify Fig 2 flow chart of movement object extraction
400

3. Movement target in the judgment process is divided into the Table 2 and table 3 each represent a difference image, it can
following several steps: be seen in Table 2 that the pixel difference is not much, so it
can be concluded that the two pictures did not change and
(1) to take three successive frames of image difference adaptive method to obtain the threshold is also small. The pixel
image and threshold; difference in Table 3 is large, it can be concluded that
(2) to determine whether threshold is more than 20 or movement object exits and adaptive method to obtain the
difference of threshold is more than 10, if a jump to (7 )or not threshold is large too.
to jump to ( 3);
(3) to capture image difference and threshold of three V. SUMMARY
consecutive image frames; This paper focused on the study of information processing
and movement information detection based on the platform of
(4) to determine whether threshold is more than 20 or
ARM+Linux. The main results are as follows:
difference of threshold is more than 10, if a jump to (7 )or not
to jump to ( 5); (1) a video surveillance system is developed based on the
embedded development platform of ARM+Linux, which could
(5) to calculate respectively difference image and threshold
be widely used for using USB camera. The results show that,
of two three frame image;
the platform has stable performance, it is easy to use and
(6) to determine whether threshold is more than 15, if a expand, and the image information acquired by the picture is
jump to (7 )or not to jump to ( 5); relatively clear. so it is accord with future development trend of
video monitoring application.
(7) to alarm to the user and jump to ( 1).
(2) using median filter to process image and the de-noising
3, to determine whether there is a movement object effect is much better.
according to threshold.
(3) the modified three frame difference algorithm is used
The threshold represents characteristics of a difference for image processing. the method observe the threshold size of
image. That the threshold is more representative of the two moving objects and moving objects under the condition and
images of the poor more, and it can determine whether a then judge the difference image threshold to identify whether
movement object exists. Table and table can shows it as there is a moving object method. The experimental results
follows: show that the extraction effect of moving target information is
quite good.
TABLE II. PIXEL ROWS LIST
1 2 0 1 1
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