Gesture Based Character Recognition

Gesture is rudimentary movements of a human body part, which depicting the important movement of an individual. It is high significance for designing efficient human-computer interface. An proposed method for Recognition of character(English alphabets) from gesture i.e gesture is performed by the utilization of a pointer having color tip (is red, green, or blue). The color tip is segment from back ground by converting RGB to HSI color model. Motion of color tip is identified by optical flow method. During formation of multiple gesture the unwanted lines are removed by optical flow method. The movement of tip is recoded by Motion History Image(MHI) method. After getting the complete gesture, then each character is extracted from hand written image by using the connected component and the features are extracted of the correspond character. The recognition is performed by minimum distance classifier method (Modified Hausdorf Distance). An audio format of each character is store in data-set so that during the classification, the corresponding audio of character will play

Gesture-based Numeral Extraction and Recognition Shree Prakash

In this work the extraction of numerals and recognition is done using gesture. Gestures are elementary movements of a human body part, and are the atomic components describing the meaningful motion of a person. It is of utmost importance in designing an intelligent and efficient human-computer interface. Two approaches are proposed for the extraction of numeral from gesture. In the first approach, numerals are formed using the finger gesture. The movement of the finger gesture is identified using optical flow method. A view-specific representation of movement is constructed, where movement is defined as motion over time. A temporal encoding is performed from different frames into a single frame. To achieve this we utilize motion history image (MHI) scheme which spans the time scale of gesture. In the second approach, gesture is performed by the use of a pointer like a pen whose tip is either red, green, or blue. In the scene multiple persons are present performing various activities, but our scheme only captures the gesture made by the desired object. HSI color model is used to segment the tip followed by the optical flow to segment the motion. After getting the temporal template, the features are extracted and the recognition is performed. Our second approach is invariant to uninteresting movements in the surrounding while capturing the gesture. Hence it will not affect the final result of recognition