Joint Template Matching Algorithm for Associated Multi-object Detection

Abstract

A joint template matching algorithm is proposed in this paper to reduce the high rate of miss-detection and false-alarm caused by the traditional template matching algorithm during the process of multi-object detection.The proposed algorithm can reduce the influence on each object by matching all objects together according to the correlation information among different objects.Moreover, the rate of miss-detection and false-alarm in the process of single-template matching is also reduced based on the algorithm.In this paper, firstly, joint template is created from the information of relative positions among different objects.Then, matching criterion according to normalized cross correlation is generated for multi-object matching.Finally, the proposed algorithm is applied to the detection of watermarks in bill.The experiments show that the proposed algorithm has lower miss-detection and false-alarm rate comparing to the traditional NCC algorithm during the process of multi-object detection.