Making overexposure work for you part I

Making overexposure work for you part I
Dr Ajay Kumar Singh / Shutterstock

Overexposure is the effect when optical sensor reaches saturation and from that point on, only the maximum pixel value (usually 255) is shown. Overexposed objects can cause a lot of headaches in image processing, but there are ways in which it can be made useful. 

For OCR, bar code and similar applications it can be useful to overexpose the image to eliminate the noise or dirt, since the printed part is usually darker than the impurities. In the image bellow we see a printed text scribbled over with a graphite pencil.

If we were to try preprocessing the image with a filter or histogram equalization, results would not be satisfying:

Instead we could gradually increase the exposure until the scribbles are eliminated:

There might be a need for adjusting different exposure for every line, but the results are quite convincing. One fact should be taken into account when using overexposure and that is that object will change their edges and become “thinner” like we see it in the next image.

From this image it is quite clear that overexposure should be avoided for applications that require precise measurement.