Geometric shape detection and classification in 2 D images on raspberry pi module - 3 -- 2

Project is geometric shape detection in 2 dimensional image on raspberry pi module 3. I have made my progrom in matlab software now I need to convert it into python to make a stand alone application. Image is captured from camera module interfaced with Raspberry pi and processed. Reading that image we are for each blob we have to detect what is shape of that region by measuring the distance between shapes centroid and boundary. we decide what is number of vertices like triangle will have three vertices, pentagon will have 5 vertices like wise. General Overview of My algorithm: 1. Take image using camera interfaced to raspberry pi (Rpi) 2. For a single shape create a centroid to boundary distance profile (Please check the image of centroid to boundary distance profile in attached file) 3. Based on that profile classify these shapes into individual one 4. Also using that profile measure the length of each vertices if shape have vertices between two-to-six and radius and major and minor axis if it is circle or ellipse respectively 5. We need to measure all basic properties of each shape using that profile. 6. So you need to do detection, classification, counting, and measuring properties for each shape 7. Plot detection vs distortion i.e. the accuracy how it behaves against distortion (using synthetic image) 8. Plot time taking for each shape detection Program steps will be like this: Different shapes to be classified are: 1-Ellipse 2-equilateral triangle 3-Iso-scale triangle 4-Right triangle 5-Ir-regular triangle 6-Rhombus 7-Irregular rectangle 8-Regular rectangle 9-Square 10-Regular Pentagon 11-Irregular Pentagon 12-Regular Hexagon 13-Irregular Hexagon 14-Circle … etc