3-D object recognition and restoration independent of the translation and rotation using an ultrasonic sensor array, neural networks and invariant moment are presented. Using invariant moment vectors on the acquired 16x8 pixel data, 3-D objects can be...
3-D object recognition and restoration independent of the translation and rotation using an ultrasonic sensor array, neural networks and invariant moment are presented. Using invariant moment vectors on the acquired 16x8 pixel data, 3-D objects can be classified by SOFM(Self Organizing Feature Map) neural networks. Invariant moment vectors kept constant independent of the translation and rotation. The experiment result show that the proposed method can be applied to the environment recognition.