1 / 12

Road sign recognition with the e-puck

Road sign recognition with the e-puck. Signals, Instruments and Systems – Project. Kim Ehrensperger & Alain Fuglister - SIE - BA VI 06-10-2011. SIS Project: Road sign recognition with the e-puck. Road Signs. Positive signs. Negative signs. SIS Project: Road sign recognition with the e-puck.

garima
Download Presentation

Road sign recognition with the e-puck

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Road sign recognition with the e-puck Signals, Instruments and Systems – Project Kim Ehrensperger & Alain Fuglister - SIE - BA VI 06-10-2011

  2. SIS Project: Road sign recognition with the e-puck Road Signs Positive signs Negative signs

  3. SIS Project: Road sign recognition with the e-puck Recognition Algorithm Vectors operations Boolean conditions Recognition Sensibility parameter Reaction behaviour This flowchart represents the different steps implemented

  4. k=0; for (i=0; i<40; i++) { mean_rows[k] = 0; for (j=0; j<1600; j=j+40) { h=i+j; buf = (unsigned int)(unsigned char) pic[h]; mean_rows[k] = mean_rows[k] + buf; } mean_rows[k] = mean_rows[k]/40; k=k+1; } k=0; for (i=0; i<1600; i=i+40) { mean_cols[k] = 0; for (j=0; j<40; j++) { h=i+j; buf = (unsigned int)(unsigned char) pic[h]; mean_cols[k] = mean_cols[k] + buf; } mean_cols[k] = mean_cols[k]/40; k=k+1; } SIS Project: Road sign recognition with the e-puck Vectors operations for (i=0; i<1600; i++) { mean_pic = mean_pic + (unsigned int)(unsigned char)pic[i]; } mean_pic = mean_pic/1600; for (i=0; i<40; i++) { norm_rows[i] = mean_rows[i] / mean_pic; norm_cols[i] = mean_cols[i] / mean_pic; }

  5. for (i=0; i<40; i++) { if (norm_rows[i]<(1-sensi) || norm_rows[i]>(1+sensi)) hori = 1; else if (norm_cols[i]<(1-sensi) || norm_cols[i]>(1+sensi)) vert = 1; } SIS Project: Road sign recognition with the e-puck Boolean conditions, Recognition andSensibility parameter sensi=0.25; if (mean_pic<40) sensi=0.1; cross = hori+vert== 2; crash = hori+vert ==0;

  6. Wait function used to make the LEDs blink SIS Project: Road sign recognition with the e-puck Reaction behaviours examples Horizontal or vertical void wait(unsigned long long int num) { unsigned long long int i; for(i=0; i<num; i++) __asm__ volatile("nop"); } while(b<10){ If (hori==1 && vert==0) { e_set_led(5,1); e_set_led(6,1); e_set_led(7,1); wait(200000); e_set_led(5,0); e_set_led(6,0); e_set_led(7,0); wait(200000); } else if (vert==1 && hori==0) { e_set_led(1,1); e_set_led(2,1); e_set_led(3,1); wait(200000); e_set_led(1,0); e_set_led(2,0); e_set_led(3,0); wait(200000); } … Conditions of too low luminosity if (mean_pic<30) { while(f<5) { e_set_led(0,1); wait(100000); e_set_led(0,0); e_set_led(1,1); wait(100000); … …. e_set_led(7,1); wait(100000); e_set_led(7,0); f=f+1; } while(1) { }; }

  7. SIS Project: Road sign recognition with the e-puck Demonstration Warning Now, pay attention to the setup please. It’s this cardboard thing which is placed on the table...

  8. SIS Project: Road sign recognition with the e-puck Exemple of pictures taken by the e-puck Angle: 45° Distance: 25 [cm] Angle: 27° Distance: 50 [cm] Angle: 0° Distance: 80 [cm]

  9. SIS Project: Road sign recognition with the e-puck Exemple of pictures taken by the e-puck • Angle max: 70° • Distance: 35 [cm] Minimum of luminosity ( ~10% of the grey scale)

  10. SIS Project: Road sign recognition with the e-puck Results Very few errors because we have defined limits to our recognition process. High succes rate due to a well calibrated setup: • Luminosity : lower threshold • Distance : max 80 [cm] • Angle : max 70 [°] • Framing : position of the e-puck and size of the signs Quantitative results are not so interesting because the errors don’t come from the recognition algoritm. The detection of the sign is the main source of error but is not in the scope of this project.

  11. SIS Project: Road sign recognition with the e-puck Conclusion Good recognition depends on: • Luminosity • Distance • Angle • Resolution of the picture Our high success rate is due to: • The use of simplified road signs • A non-moving system • An accurate setup calibration

  12. SIS Project: Road sign recognition with the e-puck

More Related