Representative algorithms for extracting gradient features include HOG (histogram of oriented gradients)

Shapelet and Edgelet. They have been widely used in the fields of object detection

object recognition

image retrieval

and scene classification. A new feature named Multi-Directional Integration of Gradients (MDIG) is proposed after analyzing the HOG and its fast version. By avoiding computing the gradient orientation and using an integral image

the new feature is easier to extract and can be hardware implemented on a DSP.The MDIG is tested on images of human head-shoulders. Using AdaBoost to train a classifier

the result is comparable with HOG

while the computation burden is only one third of that of the HOG. Finally

the use of gradient feature is discussed

and the future work is summarized.