review of hardware requirements in image processing based quality testing of object

International Journal of Emerging Technologies and Engineering (IJETE)

Volume 1 Issue 11, December 2014, ISSN 2348 – 8050

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Review of Hardware Requirements in Image Processing

Based Quality Testing Of Object

Ms.Swati S. Pawar1, Miss. Pooja Shinde

2, Miss.Neha Zawar

3

1Assistant Professor E&TC SITRC, Nasik, Savitribai Phule Pune University Maharashtra India

2,3Student E&TC SITRC, Nasik Savitribai Phule Pune University

Abstract— Quality Control or QC is a process in which

entities review the quality of all factors under

production. Control involves inspection of products

visually using stereo microscope and comparing results

with the description of unacceptable products to

uncover the defects and determination of allowance or

rejection of product release. On he other hand Quality

Assurance or QA focuses on preventing mistakes or

defects in manufactured product. These aspects are time

consuming and sometimes inaccurate when done

manually. To overcome such drawbacks automized

method for testing is very important. This paper

reviewed the method for testing of objects automatically

by using the captured images of objects and applying

various image processing techniques such as contrast

enhancement, pre-processing, background subtraction

and morphological operators. This method is more

efficient, more accurate and require less time. In this

paper we are going to review hardware part required in

project.

Keywords—Open CV, image enhancement,

Geometrical properties Background subtraction,

segmentation, morphological operation, contours in

image

I. INTRODUCTION Quality assurance refers to administrative and

procedural activities implemented in a quality system to

meet the requirements and goals of product or service.

Quality control focuses on process output. Ultimately

suitable quality is determined by users or customers.

In present day industry have lot of manually

operated processes. Manufacturing process includes

welding, cutting, molding of metal job etc. Being

specific about the industry we dealing, the parameters

testing of product is completely manual process. Output

products quality and precision puts the entire system at

risk hence there is no chance of any human error in the

parameters being measured. These calculations are

carried out by labor using traditional measuring

methods such as:

1. Vernier caliper

2. Snap gauge

3. Air plug gauge

These methods are precise but involve risk of

human errors which depend on the skill of labor used.

Any minute error in the measurement may result into

some major problems in working of the main machine it

is part of. This will affect the overall production time

required to manufacture the jobs. Our work strives to

develop a technique which will cancel all the manual

process of measurement. This will ease the industry

officials from the strenuous techniques of measurement

for each and every job. This will surely reduce the work

load. The advantages of the project to the industry are:-

1. Because of automization man power reduces

2. This method gives more accuracy than manual work

3. This method is highly efficient

4. Time consumption reduces because of automization.

5. It does not require continuous attention

For this prototype model we consider Water Pump

Pulley and nuts & bolts as objects to be tested. The

work deals with the automation of object testing using

Image Processing techniques like: image enhancement,

image subtraction, segmentation and morphological

operations, instead of any human intervention during

testing [1].

Objects to be tested:

1. Nut & Bolt

2. Water Pump Pulley

Figure.1 Nut & Bolt Figure.2 Water pump pulley

II. FINALIZED SOFTWARE

TECHNIQUES OpenCV:

In this project we are checking quality of object

using Image Processing. Instead of Matlab we will use

OpenCV Software.

OpenCV (Open Source Computer Vision) is a

library of programming functions mainly aimed at real-

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time computer vision. OpenCV also include statistical

machine learning library.

OpenCV is written in C++, Python , Java. OpenCV

runs on Windows, Android, and Linux etc.

1. Image Enhancement: It is among the simplest and most appealing areas of

digital image processing. Image enhancement is the

process by which we try to improve an image so that it

looks subjectively better [2].

Contrast Stretching:

It is a simple enhancement technique. In this method

contrast in an image is improved by stretching the range

of intensity values.

A. Original Image B. Contrast stretched image

[3]

Figure 1.1: Contrast Stretching

2. Image Subtraction: In background subtraction we detect moving object

in videos using static cameras.

Frame Difference Technique: In this technique the current frame is simply

subtracted from the previous frame and if the difference

in pixel values for given pixel is greater than threshold

then pixel is consider part of foreground. [4]

A. Original colour video B. Gray scale image

C. Background image D. Gray scale - Background

image

[14]

Figure 2.1: Background subtraction using frame

difference technique

3. Image segmentation: Segmentation is nothing but making the part of

image or any object.

Thresholding: Image thresholding is one of the effective technique

among various techniques of image segmentation. The

techniques of image segmentation based on

thresholding includes color image thresholding,

thresholding by region growing, region splitting and

thresholding in various color spaces. Among all these

techniques the most effective technique which is

suitable for our project is color thresholding along with

background subtraction. Although thresholding does not

result with the efficient output using morphological

operations the noise caused by thresholding can be

eliminated [5].

4. Morphological Operation: Morphological operations are one of the efficient

techniques in image processing which can yield better

results than any other techniques. The focus of ours in

using morphological techniques is because of its several

algorithms that are very useful in eliminating the

undesired data. Morphological edge detection is well

fast and efficient than normal edge detection because

the results that is obtained from the morphological edge

detection does not contain much discontinuities as

compared to the normal techniques and this prevents us

in eliminating the fake results we may get developed if

the application is concerned with the number of objects

in an image [6].

[6]

Figure 4.1: Results after applying Morphological

Operations

Contours: Contours are basically defined as those properties

which helps in defining the shape of an object. In our

project the concept of contours comes in picture by

considering the features by which the objects can be

recognized and the further processing part can be

implemented. Using counters the features of an objects

such as Area, Perimeter, Connectivity, Bounding




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Rectangle, Minimum enclosing circle, and etc can be

extracted and the data can be used for further

processing.

III. REQUIRED HARDWARE

1. Power Supply:

The ac voltage, typically 220V, is connected to a

transformer, which steps down that ac voltage down to

the level of the desired dc output. A diode rectifier then

provides a full-wave rectified voltage that is initially

filtered by a simple capacitor filter to produce a dc

voltage. We are using W10M rectifier IC. This resulting

dc voltage usually has some ripple or ac voltage

variation. A regulator circuit removes the ripples and

also retains the same dc value even if the input dc

voltage varies, or the load connected to the output dc

voltage changes. This voltage regulation is usually

obtained using voltage regulator 7805 IC.

2. Microcontroller:

Microcontroller is used to control the hardware in

the system.

AT89s51: The AT89S51 is a low-power, high-

performance CMOS 8-bit microcontroller which

includes 4K bytes of In-System Programmable Flash

memory. It is manufactured using Atmel’s high-density

nonvolatile memory technology. It has provides

following standard features:128 bytes of RAM, 32 I/O

lines,4K bytes of Flash, two 16-bit timer/counters,

Watchdog timer, two data pointers, full duplex serial

port, on-chip oscillator, and clock circuitry [7].

AT89C51: It is a High performance CMOS 8 bit

microcontroller. It has a non volatile memory which is

an important factor. IT is compatible with industry

standards. Its memory is reprogrammable. It is highly

flexible and cost effective in embedded applications [8].

3. USB to TTL converter: It is used to transmit data serially from laptop to

microcontroller. It is a small but very powerful USB to

TTL converter module which is built around

PL2303HX. This module uses male USB connector. Its

output is channeled through 5 pins which are GND,

RXD, TXD, 5.0V, 3.3V. This module works as USB to

Serial converter by creating virtual com port in

computer [9].

[7]

Figure 3.1: USB to TTL converter

4. USB to RS-232 Converter:

It is a USB to Serial converter which plugs into PC's

USB port and gives hardware serial port as output. It

can be operated at 3.3V as well as 5V logic and its pins

are compatible with FTDI cable header. It has a power

LED which illuminates when serial port is powered.

Figure 4.1: USB to RS232 converter

5. Relay driver circuit:

This circuit is used for driving the SPDT relay [13].

The output current of microcontroller is about 25mA

which is not enough for relay to activate hence this

current is amplified in order to meet current requirement

by relay. For amplification either ULN2003 or BC547

can be used. As only one relay is to be driver BC547

can serve the purpose.

BC547: It is an NPN bi-polar junction transistor.BC547 is

mainly used for amplification purposes. It has a

maximum current gain of 800. The input signal at base

is amplified and taken at the emitter. BC547 is used in

common emitter configuration for amplifiers. [10]

ULN2003:

The ULN2003AP/AFW Series are high voltage,

high current Darlington drivers comprised of seven

NPN Darlington pairs. All units feature integral clamp

diodes for switching inductive loads. Applications

include relay, hammer, lamp and display (LED) drivers

[11].

6. Motor Driver Circuit:

Motor driver circuit is used to control the DC

motor. It involves the action of SPDT. Motor is

connected to normally open (NO) terminal of the relay.

Normally closed (NC) is connected to ground. When

Positive acknowledgement comes from microcontroller,

relay will trip from normally open to normally close and

hence the motor will drive.




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Figure 6.1: Motor Driver Circuit

Freewheeling Diode: A freewheeling diode is generally used to protect

the device from being damaged due to reverse current

of the inductive load. When current through inductor is

interrupted, it reverses the polarity & increase the

voltage to maintain the current. Without a freewheeling

diode the voltage can damage the device. So the diode

allows the reverse current flow through it and

dissipates.

7. DC motor:

We need DC motor to drive the conveyor belt and

mechanical pusher. It is a low cost DC motor normally

used for robotic and general applications. It has a shaft

with a hole for mounting of wheels or pulleys. The DC

motor we are using is having input voltage in range 6-

12V, 30 RPM, current rating 500-600mA & shaft length

2.4cm

Figure 7.1: DC Motor

8. Conveyor belt:

Conveyor belt is used to carry the objects. It

consists of 4 wheels and a rubber belt which covers the

wheels. Pair of wheel is driven by DC motor and due to

rubber belt all four wheels will be rotating in same

direction. In this system we require three platforms for

placing IR sensor, 2 cameras which will be capturing

the images horizontally & vertically and a mechanical

pusher.

9. IR sensor: IR sensor is nothing but a pair of transmitter and a

receiver. It is used to determine whether object is

present or not. Transmitter consist a LED which emits

Infrared radiations continuously. If there is any obstacle

then the radiations are reflected back and detected by

photodiode present at receiver. Photodiode generates

analog output so for converting it to digital a

comparator is used.

10. Camera: Camera is used to capture the images of object

horizontally and vertically. We are using Logitech

webcam C170. This is a 5 MP camera having built in

mic with noise reduction. It has high speed USB 2.0. It

has a clip which fits Laptop, LCD, etc.

Figure 10.1: Camera

11. Mechanical Pusher:

Rack and pinion: Rack and pinion assembly is nothing but a pair of

gears. It converts rotational motion into linear motion.

Circular gear is called as pinion and linear gear is called

as rack. A DC motor is used to drive the pinion. L293D

will be used to drive the DC motor in both directions

i.e. clockwise and anti-clockwise. This will work as

pusher which will be used for discarding the defective

object.

Figure 11.1: Rack & pinion assembly




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IV. CONCLUSION From reviewed paper use of contrast stretching,

thresholding, morphological operations as well as use of

contours gives better result. For hardware system requires 5V power supply for

functioning. It comprises of a step down transformer.

Rectifier IC W10M is used due to its high current

capability, strong & stable performance. 7805 regulator

IC is used as its 5V supply provides convenient power

source also it is economical & saves space. The

microcontroller AT89s51 is used due to its ISP features

that reduce need of program downloader. For serial

communication USB-TTL module is used since it is fast

and gives better response. One relay is to be driven

hence transistor BC547 is used as its enough to energize

relay coil considering its current requirement. SPDT

relay is taken into consideration. The use of SPDT relay

will be efficient to drive the DC motor. IN4007

freewheeling diode is used to prevent relay from

damage. 6-12V, 30 RPM DC motor is used to drive

conveyor belt & mechanical pusher of rack and pinion

assembly. IR sensors are used to detect presence of

object & two cameras are used to capture suitable object

image.

The paper concludes that the use of above

mentioned components makes system work more

efficiently to get desired results.

REFERENCES

[1] Mrs.A.H.Tirmare, Ms. R. N. Kulkarni, Mr. A. R

Bhosale, Mr. C. S. More, Mr. A. G. Nimbalkar, `Quality

testing of water pump pulley using image processing’,

ISSM 0975668X, Volume-02, Issue-02, 04,

Nov12-Dec13.

[2] Seema Rajput, S.R.Suralkar, Comparison Study of

Enhancement Technique IJCSMC, vol. 2, issue 1,

pp.11- 21, Jan-2013.

[3] Raman Maini & Himanshu Aggarwal, A

comprehensive review of image enhancement

techniques, Journal of computing, ISSN 2151-9617,

Volume-02, Issue-3, March 2010.

[4] Deepjoy Das, Sarat Sahaira, Implementation and

performance evaluation of background subtraction

algorithms. IJCSA, vol 4, no 2, April 2014

[5] H.P Narkhede, Reviews of Image Segmentation

Techniques IJISME, vol. 1, issue 8, pp. 54-61, July-

2013.

[6] Ratika Pradhan, Prasanna Pradhan, Edge Detection

Using Morphological Operator IJARCSSE, vol. 4, issue

2, pp. 84-88, February-2014.

[7] http://www.atmel.com/images/doc2487.pdf

[8] http://www.keil.com/dd/docs/datashts/atmel/

at89c51_ds.pdf

[9] http://www.ventor.co.in/index.php?main_page=

product_ info&products_id=359

[10] http://pdf.datasheetcatalog.com/datasheet/fairchild/

BC547. pdf

[11] https://electrosome.com/uln2003-high-voltage-

current- driver/

[12] www.alldatasheet.com

[13] http://www.farnell.com/datasheets/1805276.pdf

[14] R.S Rakibe , B.D. Patil, “Human Motion Detection

Using Background Subtraction” IJARCSSE, vol. 4,

issue 2, pp. 45- 48, February-2014


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