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VIDEO: larity Machine Vision Software – The Color Detection Plug-In – Part 2 and Part 2

JADAK’s machine vision cameras are capable of many different machine vision processes. In this video I’ll demonstrate another color detection tool included with Clarity 2.0 known as the Color Pixel Count tool. The Color Pixel Count tool will be appropriate, for example, when looking to detect a range of colors within an image. I’ve acquired an image here of a litmus strip type test, but this might be a blood or urine strip where a lab may be looking for a color or shade of various colors.

Using Clarity’s machine vision can result in eliminating errors associated with the visual inspection reliant on an individual. After an image is acquired, select the color detection tool at the top, and down below use the drop down box to select Color Pixel Count under type. You’ll notice an RGB wheel appears and you can use these tools to set values for hue, saturation, value and brightness. Use the cursor to move the region of interest you want to test. In this test I’ll be examining one of the squares in the resulting test area to measure its color within a range. You’ll notice that this records the number of pixels that fall within this acceptable range, in this case around 32,000.

I’m going to increase the saturation slightly and because I only want to include all of the red colors and reject the green colors, I’m going to adjust my passing range criteria to be between 10,000 and 40,000 pixels. As a result, under my step list, my tool has turned green and I’m accepting that number of pixels within my color wheel down below. In other words, the red color here is passing. If I clone this step and perform the same color analysis for the color directly next to it, which in this case is green, you’ll notice the result is only about 140 pixels, which is being rejected by the analysis that I set in the passing range criteria. So in essence, it’s passing the red color but rejecting the green.

I’ll set up one more color analysis area to measure the sample well area and make sure that it’s within an acceptable color range. In this case I’ll look for something that’s around a yellow-orange inclusive color range. So I’ve shown here how this area will pass with an acceptable number of pixels within that yellow-orange range. If for some reason this sample well registered something different, for example blue, then it would be rejected by Clarity’s color analysis tool.

From here you can save the script or click on device and save the job directly to the camera by clicking on device, and send job to device.

Check out our other videos to learn how to configure the output tool, to configure the camera to determine how to respond to each one of these criteria.

This concludes the video for Color Detection tool. Check out the other videos on Clarity 2.0.