This paper presents a new method for Bengali character recognition based on view-based approach. Both the top-bottom and the lateral view-based approaches have been considered. A layer-based methodology in modification of the basic view-based processing has been proposed. This facilitates handling of unequal logical partitions. The document image is acquired and segmented to extract out the text lines, words, and letters. The whole image of the individual characters is taken as the input to the system. The character image is put into a bounding box and resized whenever necessary. The view-based approach is applied on the resultant image and the characteristic points are extracted from the views after some preprocessing. These points are then used to form a feature vector that represents the given character as a descriptor. The feature vectors have been classified with the aid of k-NN classifier using Dynamic Time Warping (DTW) as a distance measure. A small dataset of some of the compound characters has also been considered for recognition. The promising results obtained so far encourage the authors for further work on handwritten Bengali scripts.