Extracting image orientation feature by using integration operator
This paper presents an orientation operator to extract image local orientation features. We show that a proper employment of image integration leads to an unbiased orientation estimate, based on which an orientation operator is proposed. The resulting discrete operator has flexibility in the scale selection as the scale change does not violate the bias minimization criteria. An analytical formula is developed to compare orientation biases of various discrete operators. The proposed operator shows lower bias than eight well-known gradient operators. Experiments further demonstrate higher orientation accuracy of the proposed operator than these gradient operators.
scale selection gradient operator feature extraction image recognition local orientation estimation orientation bias