Detecting Highly-Degraded Occurrences of a Reference Model in Multiple Files
Following this tutorial, you will learn how to use EasyFind to detect in multiple images highly-degraded occurrences of a reference model. The degradation can be due to noise, blur, occlusion, missing parts or unstable illumination conditions.
Load the reference image
Create an ROI to define the reference model on the reference image
Improving the Score of Found Instances by Using Do Not Care Areas
Following this tutorial, you will learn how to use EasyFind to handle “don’t care areas” in geometric pattern matching. “Don’t care areas” help to define in the image the meaningful features only, by masking the areas that might change from image to image, such as text and numbers.
Loading the reference image
Creating an ROI to define the reference model on the reference image
Learning the reference model
Setting a rotation tolerance
Detecting instances of the reference model without “don’t care areas”
Defining the “don’t care area”
Detecting instances of the reference model with “don’t care areas”