Turkish Fingerspelling Recognition System Using Axis of Least Inertia Based Fast Alignment

Fingerspelling is used in sign language to spell out names of people and places for which there is no sign or for which the sign is not known. In this work we describe a Turkish fingerspelling recognition system that recognizes all 29 letters of the Turkish alphabet. A single representative frame is extracted from the sign video, since that frame is enough for recognition purposes of the letters mentioned. Processing a single frame, instead of the whole video, increases speed considerably. The skin regions in the representative frame are extracted by color segmentation in YCrCb space before clearing noise regions by morphological opening. A novel fast alignment method that uses the angle of orientation between the axis of least inertia and y axis is applied to hand regions. This method compensates small orientation differences but increases big ones. This is desirable when differentiating the fingerspelling signs, some of which are close in shape but different in orientation. Also the ...

• Type: Conference
• Year: 2006
• Where: AUSAI
• Authors: Oguz Altun, Songül Albayrak, Ali Ekinci, Behzat Bükün
• Keywords: Artificial Intelligence, AUSAI 2006, Minimum Bounding Square, Representative Frame, Turkish Fingerspelling Recognition