The video scenes are carefully picked that can show the effect of image processing techniques to the full.

Here is the grayscale switches that are required.

This is the gaussian blur, increasing the filter kernel will take adjacent pixel gray values into account, the bigger kernel you have, the larger this range of "merging" will be.

Bilateral filter can blur the images while preserving the boundary features. Especially for objects like comb,tree stems, textures on the surfaces were blurred while edges were preserved.

To grab the orange, color thresholding was used to pick out designated colors.

Improvement was made by applying morphological open operation and we show it in cyan.

For Sobel,we first use CV_16U unsigned, thus only two gradient-dropping edges will be detected (right, bottom)

Then we change to CV_16S signed, then all edges will be detected (up,bottom,left,right), we can also increase delta value to make the edge easier to be detected.

Lastly, we can increase the scale of sobel to make gradient drop/climb even more drastic to address the presence of boundaries.

Here we first use small threshold values for only bottlecap, with three different setups, first is with a resolution scaling rate 1 and circle distance one-fourth of the image height. We can see bottlecap got captured correctly and without redundant circles.

Second, we use a very low circle center distances, clearly a lot of redundant circles roughly at same place were detected.

Then we roll back circle distances and give scaling factor 10, which scales video frames to one-tenth the original resolution. Obviously with a lower resolution, more false circles are detected.

Here we change the threshold to higher values to capture orange and avoid bottlecap. First, we use a low param2 value which gives us multiple circles, lower param2 value means loose restriction.

Then we raise param2 to a more reasonable value, which gives us perfect orange detection.

Lastly, we switch between high param1 and normal param1, when increasing param1, less circles are detected, which means a more strict requirement for circle detection.

Now we draw the attention of audience with flashy/colorful bounding box to our target, the bottlecap.