How to detect patterns on a 1D array of measurements

I am developing an IA algorithm for a robot that needs to follow a line. The floor will be black, with a white line and there will be different marks that determine different types of "obstacles". I'm using a sensor that gives me an array of 8 measurements of the floor, as seen on the Figure 1 that give me an array of 8 measurements from 0 to 1000, where 0 there is no white and 1000 is totally white. In the examples bellow is a measurement of a white line in the middle of the sensor array and other cases.

int array[] = {50, 24, 9, 960, 1000, 150, 50, 45} // white line in the middle
int array2[] = {50, 24, 9, 960, 1000, 150, 50, 960} // white line in the middle and a square box on the right
int array3[] = {1000, 24, 9, 960, 1000, 150, 50, 40} // white line in the middle and a square box on the left
int array4[] = {1000, 980, 950, 0, 10, 980, 1000, 960} // black square box in the middle

Witch algorithms I could use to detect the patterns on the images below given this array of measurements? I do not want to use several "hardcoded" conditionals as templates, as I think it will not scale well. Im thinking on implementing a "peak counter" algorithm, but I do not know if it will work robust enough.

On the Figures we can see the different cases, the case I want to detect are the ones with the red circle.

Thanks!