Machine Vision System

The selection of vision system depends on a number of factors such as the environment, the exact task, and the type of objects etc. Selection of a universal test system which will satisfy all the required criteria is not unique and are application oriented. Choice of objects to be tracked and the process environment where the system is to be installed are two major essential requirements for establishing a stable system. Figure 3.3 provides a detailed description about the basic system parameters and conditions for choosing a MV system.

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Figure 3.3: Selection Criteria for a Machine Vision System

A vision processor is a class of microprocessor which is designed to perform specific task and acted as an accelerator for vision tasks. Direct interfaces are available in a vision system. Consequently, data can be extracted from several cameras and on-chip dataflow among many parallel execution units can be performed. The vision processor used in this research work is NI PXIe 1082 as shown in Figure 3.4 and the technical specifications are given in Table 3.3 [www.ni.com/pdf/manuals/372752b.pdf]. This processor has interfaces for other sensors and data acquisition devices.

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Figure 3.4: NI Machine Vision Processor (Model: NI PXIe 1082)

Table 3.3: Technical Specification of NI Machine Vision Processor

Control System Model

PXI platforms NI PXIe-1082

X series Multifunctional DAQ NI PXIe-6341

Motion Controller NI PXI-7340

1394 Host Adapter NI PXI-8252

NI Compact RIO NI cRIO-9074

Dual GBEthernet NI 8234

4-Ch Universal Analog Input DAQ NI 9212

16-Ch, 24 DI/DO DAQ modules NI 9375

8-Ch,TTL High speed DIO DAQ NI 9401

ATI DAQ Module FTPS1

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D. Camera

The image acquisition is a complex interaction of the material and surface characteristics of the test object and the lighting used. The vision sensor (camera) plays an important role in acquiring the image and can be termed as "detector unit". An image is captured by the sensor and is processed by the vision processor. The selection of camera depends on the required accuracy and speed of the inspection as well as the application area.

There are two types of cameras available i.e. charged couple device (CCD) and complementar y metal oxide semiconductor (CMOS). A CCD camera creates high quality and less noisy images. It requires analogue to digital converter as the output signal is analogue in nature. It consumes more power and costs high. But a CMOS camera does not require any converter as the output signal is digital one. CMOS type camera are more susceptible to noise, but consumes less power and is economic. The speed of a CCD camera is ranging from moderate to high, whereas CMOS camera speed is high. This choice really depends upon the particular application requirements.

Types of industrial cameras

• Line scan cameras: This camera has a single row of pixel sensors. The lines are continuously fed to a computer that joins them to each other and creates an image. This is usually performed by connecting the camera output to a frame grabber. Buffering of images as well as preprocessing of images is sometimes performed by the frame grabber. A suitable number of individual lines are captured in a very quick succession by one single such camera.

• Area scan camera: This type of camera contains a matrix of pixels that capture an image of a given scene. They are more general purpose than line scan cameras, and offer easier setup and alignment. Area scan cameras are best suited towards applications where the object is stationary.

• Intelligent cameras: This type of camera performs the complete process within it i.e., from image acquisition to store image data. After that, several interfaces and protocols are utilized to transfer the stored information to a robot. These types of cameras are mainly area scan cameras and sometimes line scan cameras.

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Criterion to select an appropriate camera

The selection of camera solely depends on the type inspection task. The features to be extracted should be represented in such a way that the features can be reasonable evaluated by the software.

• Camera Type: Development of a successful application environment depends on the correct type of camera. Based on the category of task, the type of camera is selected. Area scan camera captures the image either in continuous or triggered mode whereas the seamless scanning of objects are performed by the line scan camera.

• Resolution and sensor size: Area scan cameras generate digital images comprised of pixels which correspond to some area that the camera “sees”. Since a pixel is the smallest individual unit that the camera can detect, this is the baseline for selecting camera resolution.

A general rule,

Resolution=(Area to be viewed) ⁄ (Size of object)

In case of large size components, high resolution camera is needed. However, the size of camera solely relies on the application environment.

• Speed of frame rate: Speed of a camera defines the number of images or lines per second that the camera captures. Fast communication interfaces are needed for fast cameras. In terms of frame rate the CMOS type sensors outperform the CCD sensors. • Quality of image: CCD sensors provide higher quality images than CMOS. The choice

between CCD and CMOS determined by application requirements. For several applications, CMOS will be good enough. CCD camera yields homogenous images. These images are sensitive to lighting conditions yet inclined to spreading and blooming in case of overexposure. CMOS cameras usually have need of more light and require calibration (dark and bright image). CMOS type produces images which are more inhomogeneous in nature. But, they are robust to different lighting conditions. They do not display any spreading and blooming like CCD cameras.

• Monochrome or color sensor: Number of bits required for image data to represent distinguishes the sensor type as monochrome or color. Monochrome camera use 8-bit representation format to code the image data and are prone to lighting conditions. Color images require 24-bit and involve additional processing to distinguish different

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colors of the identical brightness. The volume of data in color sensor is much larger than monochrome.

• Transmission interface: Selection of interface depends on the bandwidth required. The bandwidth (per second) required can be calculated by multiplying the bit depth, frame rate and image size. The interface must be efficient enough to communicate the image data to the processing unit reliably. Simultaneously the software used should be capable of integrating the interface to the associated camera.

• Mechanical dimensions and form factor: The dimension and form factor cannot be overlooked while selecting the camera. The camera to be used must fit into the system to be developed. As many cameras are available in the market, so the choice is wide.

Lenses

Selection of lenses is playing an important role in optimizing the use of high performance camera. The machine vision lenses can be classified into two broad categories:

• Lens for Field of view (FOV) that is much larger than camera sensor size • Lens for Field of view that is smaller than camera sensor size.

In industrial applications, the lenses are available with either fixed focal distance or a variable focal distance. Generally, there are 3 factors that governs the lens selection such as FOV, working distance and sensor size of the camera. The focal length required for the application can be estimated as:

Focal Length=(Magnification × working distance)⁄(1+Magnification) Where, Magnification of an image acquired = ((Sensor Size of the camera)) ⁄FOV

The cameras as shown in fig. 3.4 and lens are chosen by considering the above cited criteria. For acquiring image in the present work, BASLER CSA640-70gc and 7fc model camera is used. The technical specification is given in the Table 3.4.

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Camera model

Resolution

(H x V pixels) Sensor Frame Rate Mono/Color Interface scA640-70gc

(Make: BASLER) 658 x 492 ICX424 70 fps Color GigE

scA640-70fc

(Make: BASLER) 658 x 492 ICX424 71 fps Color FireWire

There are several other necessary sensors required for accomplishing several task and the sensors required for such tasks are given in the Table 3.5.

Table 3.5: Sensors associated with different activities

Activity For

Measuring

Types of Sensor

Detection

Pressure Electromagnetic, Optical sensor, Infrared Ranging, Vision Sensor

Range or distance

Triangulation (Range), Structured Light ing (Range), Ultrasonic sensors, LADER (Light Detecting and Ranging)

surface Measurement

Textures Touch sensor, Proximity capacitive sensor, Proximity Sensors, Capacitive-based sensors Softness or

Hardness

6-axis force sensor, Net-structure Proximit y Sensor

Shape

Size and

Shape

Ultrasonic sensor, Image sensor, Electric field sensing, Range image sensor

Properties

Roughness Touch sensor, Limit switches, 6-axis force sensor Magnetic

Properties

Magneto- resistive sensors

Metallic/Non -Metallic

Capacity Proximity sensor, 3-wire DC Inductive Proximity Sensor

Weight Accelerometers, Slip Sensor, 6-axis force sensor, Joint-angle sensors

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Figure 3.5: Vision Camera, Model-scA640-70gc (Make: BASLER)