Communication for Motor Neuron Disease Patients Via Eye Blink to Voice Recognition - V, Ramya; Roy, Riya; KJ, Sriraksha; K, Swathi; N, Supritha (International Journal of Computer Sciences and Engineering, 2025)
Inthispaper, we present a real time method based on some video and image processing algorithms for eye blink detection. The motivation of this researchis theneed of disabling whocannotcommunicatewithhuman. A HaarCascadeClassifieris appliedforface andeyedetectionforgettingeyeandfacialaxis information. In addition, thesame classifier is used based on Haar-likefeaturesto find out the relationship between the eyes and the facial axis for positioning the eyes. An efficienteyetrackingmethodis proposedwhichusesthepositionofdetected face. Finally, an eye blinking detection based on eyelids state (closeoropen) isused forcontrollingandroidmobilephones.The methodisusedwith andwithoutsmoothingfilter toshowthe improvement ofdetectionaccuracy. Theapplication isusedin realtime forstudyingthe effectoflightand distance between the eyes andthe mobile device in order toevaluate theaccuracy detectionandoverallaccuracyofthesystem. Testresults show that our proposed method provides a 98% over all accuracyand 100% detection accuracy for a distance of 35 cmand an artificial light.