Offline isolated bangla handwritten character recognition using spatial relationships

Handwritten character recognition is considered to be one of the most fascinating and interesting field of research in image processing and pattern recognition. Due to the various challenges associated with it, intensive research works are currently in progress for constructing algorithms that produce better recognition accuracy. This paper proposes an algorithm that recognizes offline isolated Bangla handwritten characters using spatial relationships between any foreground pixels with the background pixels. The algorithm starts with eliminating unwanted noises from scanned images, performing normalization of size and gradually progress toward constructing feature vector representation for the characters using zoning along with spatial relationships in terms of directional relationships. The constructed feature vectors for each individual Bangla character are learned into a neural network which later classifies new instance of Bangla character. The promising preliminary experimental results indicate a positive potential of our algorithm.