In this article, we introduce different techniques for improving your image-based targets by evaluating and adjusting the contrasts and other settings on the device that may impact tracking performance.
We present a series of adjustments and different techniques to help you improve low performance image-based targets. Image Targets are tracked based on their natural features which can be enhanced through the contrast settings.
Additionally, if you experience that the environment or device also impacts the tracking robustness, it may be necessary to define the camera’s focus mode and other device settings.
Evaluate a Target Image in Grayscale
Vuforia Engine uses the grayscale version of your target image to identify features that can be used for recognition and tracking. You can use the grayscale histogram of your image to evaluate its suitability as a target image. Grayscale histograms can be generated using an image editing application, such as GIMP or Photoshop.
If the image has low overall contrast and the histogram of the image is narrow and spiky, it is not likely to be a good target image. These factors indicate that the image does not present many usable features. However, if the histogram is wide and flat, this is a good first indication that the image contains a good distribution of useful features. Note, though, that this is not true in all cases, as demonstrated by the image with gradient features.