With the rise of modern technology in computer science and engineering, as well as with the growing population in big cities around the world, many new approaches for person detection have become a very interesting and demanding topic. Person detection is a necessary building block for people monitoring systems and, therefore, various detection methods must be inspected comprehensively in order to select the one with the most suitable performance and accuracy. In this paper, a set of different image processing techniques applied to images captured from a high angle were used for people detection. To be more specific, selected feature extraction techniques, like edge detectors, local binary patterns, pixel intensities or histograms of oriented gradients, were used in combination with several classification algorithms. The combinations of each feature extractor and its best classifier were selected for performance comparison. As a result of the comparison, the most suitable image processing method for person detection in high angle image is presented at the end of the paper.