In this paper, we present and analyze different approaches implemented here to resolve pedestrian detection problem. Histograms of Oriented Laplacian (HOL) is a descriptor of characteristic, it aims to highlight objects in digital images, Discrete Cosine Transform DCT with its two version global (GDCT) and local (LDCT), it changes image's pixel into frequencies coefficients and then we use them as a characteristics in the process. We implemented independently these methods and tried to combine it and used there outputs in a classifier, the new generated classifier has proved it efficiency in certain cases. The performance of those methods and their combination is tested on most popular Dataset in pedestrian detection, which are INRIA and Daimler.