  In single-pixel imaging (SPI), the target object is illuminated with varying
patterns sequentially and an intensity sequence is recorded by a single-pixel
detector without spatial resolution. A high quality object image can only be
computationally reconstructed after a large number of illuminations, with
disadvantages of long imaging time and high cost. Conventionally, object
classification is performed after a reconstructed object image with good
fidelity is available. In this paper, we propose to classify the target object
with a small number of illuminations in a fast manner for Fourier SPI. A naive
Bayes classifier is employed to classify the target objects based on the
single-pixel intensity sequence without any image reconstruction and each
sequence element is regarded as an object feature in the classifier. Simulation
results demonstrate our proposed scheme can classify the number digit object
images with high accuracy (e.g. 80% accuracy using only 13 illuminations, at a
sampling ratio of 0.3%).
