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Consumer Electronic Test   printer icon Article:  Setting Up Your Imaging Environment

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Consumer Electronic Test is an application platform created for people who need to use automated visual inspection to evaluate flat-panel displays on such equipment such as:

  • cell phones

  • PDAs

  • vehicle panels

  • computers, and more

 

 

Research, design, and validation engineers can use Consumer Electronic Test to perform detailed analysis and functional performance tests on display prototypes.

Manufacturing test managers can use the platform to perform fast, reliable, end-of-production tests with a proven system.

Consumer Electronic Test contains modules—or steps—of common display inspection tasks that you can use to build a test sequence within TestStand. TestStand is a ready-to-run test executive for organizing, controlling, and executing your automated prototype, validation, or manufacturing test system. Within TestStand, you can customize the Consumer Electronic Test steps to meet your needs, and you can integrate your own tests into the sequence.

Consumer Electronic Test contains modules—or steps—of common display inspection tasks that you can use to build a test sequence within TestStand. TestStand is a ready-to-run test executive for organizing, controlling, and executing your automated prototype, validation, or manufacturing test system. Within TestStand, you can customize the Consumer Electronic Test steps to meet your needs, and you can integrate your own tests into the sequence.

  Consumer Electronic Test Product Test Diagram

Consumer Electronic Test also ships with a library of C functions that you can use to create your own display inspection steps. In order to use these functions, you must have IMAQ Vision 6.0 for LabWindows™/CVI™ or later installed on your computer.

 

Consumer Electronic Test Steps

 

The TestStand Full Development System ships with a set of predefined steps.

Consumer Electronic Test application software adds additional steps for testing flat-panel displays and their housing. The following list describes these steps:

  • Load Simulation Image—Loads an image of a flat-panel display from file. Use this step when you want to experiment with different tests but you do not have your acquisition hardware set up.

  • Learn Calibration—Learns the perspective and lens distortion present in the image of the display. The calibration information is based on a grid template that is shown on the display. The step stores the distortion information in a calibration template.

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  • Correct Image Distortion—Corrects a distorted image by removing perspective errors and lens distortion. The step uses a previously learned calibration template to correct the image.

  • Alignment—Computes the location, orientation, and skew of the display. It also can compute the location of the housing that surrounds the display as well as the pixel gap between the display and the housing.

  • Fiducial Based Alignment—Computes the location and orientation of the display unit using user specified fiducials on the display.

  • Display Geometry—Computes the orientation and skew of the display. It also can compute the location of the housing that surrounds the display as well as the pixel gap between the display and the housing. Use this step to find information about the display when you use the Fiducial Based Alignment step to find the location of the display unit.

  • Pixel Defects—Detects defective rows, columns, or individual pixels.

  • Contrast—Computes the average intensities of the black regions and the white regions of the display and then returns the absolute difference between the mean black and mean white intensity values as the contrast of the display pixels.

  • Icon Presence—Searches for areas in an image that match a given grayscale or color icon.

  • Gross Defects—Locates, counts, and measures defects—such as scratches and blemishes—in an inspection region.

  • OCR—Reads a string of characters on the display and determines whether the string matches the expected output.

  • Segment Distortion—Locates groups, or segments, of display pixels in an image and computes the distortion of the segments.

  • Character Verification—Finds characters in the image similar to a pattern that you specify and determines the similarity between each character and the pattern.

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  • Grayscale Illumination—Divides the inspection region into rectangular bins and computes the intensity statistics for each bin. You can specify the number of bins you want to use.

  • Color Illumination—Divides the inspection region into rectangular bins and computes the color statistics for each bin. You can specify the number of bins in the inspection region and the color model you want use to compute the statistics.

  • Housing Color—Compares the color of the display housing to a color template.

  • Keypad Backlight—Computes the color statistics of the backlight.

  • Keypad Inspection—Searches areas in an image to verify that all the keys on a keypad are present and of good quality.

 

Consumer Electronic Test Steps

 

The following Consumer Electronic Test steps inspect flat-panel displays for quality pixels:

  • Alignment

  • Display Geometry

  • Pixel Defects

  • Contrast

  • Icon Presence

  • Gross Defects

  • OCR (Optical Character Recognition)

  • Segment Distortion

  • Character Verification

  • Grayscale Illumination

  • Color Illumination

By default, each of these steps displays a simulation image of a display whose pixels are in a pattern conducive for the type of inspection that the step performs. These simulation images are convenient when you want to experiment with Consumer Electronic Test to see how it works.

For your real-world application, you need to create a code module that generates patterns on the displays you want to inspect. You can incorporate the pattern generation code module into your Consumer Electronic Test application in two ways: either call the code module using a TestStand Action step, or wrap the pattern generation code module in a custom step type.

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See also: 

Consumer Electronic Test

Vision and Custom Boards

Vision Application Examples

Vision Algorithms Examples

 

 

 

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