Visual classification is a simple and self-explanatory process, at least for humans. Machines, on the other hand, have a much tougher time classifying objects in the images. Hence, classification has become one of the most engaging challenges for computer vision engineers.
If you haven’t already I recommend you read the first part before continuing with this article further. In the last article, an idea for non-linear project management was introduced. Looking at the…
Let’s imagine a situation where you want to speed up the production line which has plenty of cameras for visual inspection which work “on the fly” – without stopping the…
It is possible to take many different project management courses online or offline, but all of them, when it comes to the topic of research and development will only glance at or ignore it completely.
Background estimation is a common problem in image processing that, in some cases, could be resolved by using a simple method. If you imagine a highway with cars passing by, most of the time, the background is visible (e.g., road, trees, traffic signs) with an occasional "disturbance" in the form of a vehicle. These outliers are usually easily solved by using a median filter.
Main reason why there are so many topics related/dedicated to lights and cameras on our page is because I believe programming should always be the last resort for solving a problem. Choosing a correct light or camera could save countless hours of coding or even save a project. Coding is fun but wasting time on low quality images is often just that – wasting time. This article is written from a computer vision perspective, but it can be applied to a bigger picture.
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.
Extension methods are a great way of advancing an existing library without modifying the original class. But it is possible to do something even more powerful with it. Even the dlls of a closed source commercial library can be extended. Halcon is a commercial computer vision library which will be used for showcasing this application.
Reliably detecting colors can be a challenging task when the shape of the observed object is curved and/or has inconsistent light from all directions. In the photo shown we have dices for which we can say safely that the colors on each side should be very similar. If we were to inspect the RGB colors of left and bottom sides of the first dice (1 and 3) the results would be very different.
Because you know exactly what you're going to get if you use vectors.