Object detection based on geometric feature extracted by chord-tangent transformation

A method to extract the geometric features of planar objects was proposed by using the Chord-tangent Transformation(CTT),then a 2D object was detected based on matching the geometric features obtained by the CTT.The theoretical basis of the CTT was introduced and how to realize the method was described.Meanwhile,the errors and reliability of the method were analyzed and discussed.It was pointed out that the CTT can extract a kind of senior geometric feature from the information of edge points,and the extracted geometric feature not only has invariant characters for translation,rotation and scale,but also can obtain some important parameters such as rotation angles and movement levels.Therefore,this method solves many problems caused by the unsteadiness of gray features in complex environments and changing illumination.Moreover,it shows a robustness for the condition that there is distortion or damage in the object edges.Finally,an experiment was undertaken with some image sequences from various complex conditions,and the results show that the average accuracy of object detection is over 90%.Even if the distortion or damage of the object edges has been more than 40%,it also can offer a more accurate detection result.These results prove the effectiveness and accuracy of method.