Which language is most suitable for identifying a colored line that I know is in a picture/screendump - and translate the plotted time-serie line of the XY-plot area into an expression of variance? (how many and how big variations in the line progression from the green line appears until it ends.)
I have a challenge where I would like to understand which programming language (and package/accellerator) you think I should pursue to understand to solve this… (I hope someone suggest R or Python, so that I have a reason to learn these)
I have an output from a system where I cannot read the source values - only screendump the status screen manually. The output Log screen shows a diagram area where a green line is illustrating machines recorded output values over time since the batch was initiated. Currently we just look at it manually to evaluate if we need to clean the valves.
If the green line is swinging a lot, the system needs service.
So, which language would you choose to process the image. I imagine I will do the following:
- Crop the image (I know which area is the plotter-area of the image in which the line is identifiable
- Identify where the green line begins (e.g. from searching from the left of the cropped picture until I find one of the RGB values of the lines composition (it is “glowing” so the RGB values are 12 different nuances of green)
- somehow analyze how the line is fluctuating - my idea is to divide the 2000 pixels to steps of e.g. 100 pixels - identify the green lines vertical position at the first and last pixel of each segment. Calculate the formula (Y=aX+b), and the traverse left to right inside the 100 pixels to find the green line and see if it deviates from the straight line of the 100 pixels.
If someone can help with a smarter way to calculate the area between a straight line and the flow of this green line, I am all ears.
Looking forward to hearing you geniuses help me out
/Søren - a.k.a. Handstand