Wednesday, November 16, 2011

Smart Camera Integration in Machine Vision Systems

Smart Camera Integration in Machine Vision Systems 

Machine vision is an image-processing technology that enables automated devices to scan objects within a limited field of view, interpret their orientation, and react according to preprogrammed sequences. Smart cameras, or “machine vision sensors,” often support a machine vision system by digitizing and transferring frames for computer analysis, but some smart cameras can also serve as self-contained vision systems without relying on external processing equipment.

Unlike standard industrial or commercial cameras, smart cameras can decode the images they capture, making them less reliant on human perception. A smart camera can digitize a frame, determine if it should be communicated to a peripheral computing system, and in some cases, decide on an appropriate response to the image without resorting to outside analysis. It has a broader range of capabilities than that of traditional cameras, and can perform relatively sophisticated automated operations.

Smart Camera Specifications

Machine vision is typically a multi-staged system that employs smart cameras in the initial phases of image-processing. Although a smart camera cannot “see” with the complexity of a human eye, it can approximate vision by examining pixel clusters through pattern recognition software and drawing simple conclusions based on programmed knowledge. The components used to accomplish this include:

Sensors: Image detection equipment, such as a charge-coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS), that converts lens projections into a voltage sequence, which can then be digitized or stored in memory.

Digitization circuit: A conversion device that maps a set of points onto an image and translates them into pixels to create a digital representation.

Central processing unit: A CPU, or in some cases a digital signal processor (DSP), that executes algorithmic programs for interpreting a digital image code.

Storage hardware: Primary and secondary memory, such as RAM or Flash, used to run CPU programs, or to record and store images for future use.

Communication technology: A method for connecting cameras to external devices. An Ethernet or RS232 signal transmits encoded images to a computer for analysis, or delivers instructions to reactive equipment.

Lighting Device/LED: An illumination apparatus for clearer image captures.

Smart camera capabilities typically vary from model to model. Some types may incorporate all of the listed components, while others retain only the sensors, digital circuitry, and communication interface necessary for supporting a larger machine vision system.

Industrial Quality Control

Smart cameras are employed for a number of automated functions, whether complementing a multipart machine vision system, or as standalone image-processing units. Due to their cost-efficiency and relative ease of use, smart cameras may be an effective option for streamlining automation methods, or integrating vision systems into manufacturing operations.

In industrial production, manufacturers often use smart cameras for inspection and quality assurance purposes. A smart camera can be programmed to detect structural or component flaws, missing parts, defective or deformed pieces, and other deviations from an intended design. If networked to the proper automated equipment, such as a robotic arm or retractor, a smart camera with processing capabilities can signal the instrument to remove a defective product. Alternatively, the camera can flag a deformed product for later removal.

Smart cameras are also used for industrial measuring. Using sensors, the camera can determine and record a component’s physical dimensions without making direct contact. Depending on the vision system’s level of sophistication, these measurements can involve high precision analysis and incremental scanning. The ability to verify a product’s dimensions is also used in quality assurance to check for adherence to design specifications.

Code Reading and Identification

Code reading and authentication require less processing capacity than product inspection, so relatively simple smart camera models can perform such operations. A barcode provides machine-readable data that can be quickly scanned by a smart camera, thereby enabling a high volume of code-imprinted products to be authenticated at a comparatively rapid pace. Smart cameras can verify that a barcode has been applied to the appropriate product, or determine if a code contains the correct data.

Optical character recognition is a more complex form of code reading that requires smart cameras to identify typewritten text. The rate of authentication may be slower than that of barcode reading, but with adequate processing power, a smart camera can analyze text to a high degree of accuracy. This can be useful for ensuring that printed materials display correct spelling and word order, and that product labels conform to design.

A smart camera can provide movement correction and repositioning data when working in conjunction with an automated tool. Through a network, the camera can communicate with a robotic device to assist it with sorting or identifying parts. This process helps improve the efficiency of automated services by increasing the accuracy of part manipulation.

Other Uses for Smart Cameras

Since a smart camera’s functionality chiefly depends on its image-processing capacity, the device is adaptable to numerous requirements. Smart camera users can develop or purchase custom software programs to meet specific machine vision needs, which can range from product quality assurance to law enforcement support.

Some machine vision systems form a visual sensor network, which uses multiple smart cameras positioned at specific locations to capture images of a single object or area from several angles. This method is applied under circumstances in which numerous images fused together are more useful than the individual image each camera obtains. Sensor networks can effectively monitor environmental conditions, track objects in motion, or simulate three-dimensional representations of images.

The technology used in a smart camera has also been applied to biometric recognition systems. Retinal, facial, or fingerprint scanning are used for security purposes. A smart camera’s processor can execute programs that use recognition algorithms to verify a person’s identity or trace his location. (For more information on BioMetrics, visit the BioMetric Consortium.)

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