计算机科学 ›› 2015, Vol. 42 ›› Issue (Z6): 231-235.

• 模式识别与图像处理 • 上一篇    下一篇

不确定环境下基于SIFT算法和一类分类的火焰识别

林涛,黄继风,高建华   

  1. 上海师范大学计算机科学与工程系 上海200234,上海师范大学计算机科学与工程系 上海200234,上海师范大学计算机科学与工程系 上海200234
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家自然科学基金项目(61073163),上海市企业自主创新专项资金项目(沪CXY-2013-88),上海市教委科研创新重点项目(14ZZ125),上海师范大学研究生重点项目(SNU14001)资助

Flame Detection Based on SIFT Algorithm and One Class Classifier with Undetermined Environment

LIN Tao, HUANG Ji-feng and GAO Jian-hua   

  • Online:2018-11-14 Published:2018-11-14

摘要: 在不确定的复杂环境下,基于图像的火焰早期检测是一个未解难题。因此,将灰度均衡化理论延伸至此领域来对疑似火焰图像进行预处理,通过引入SIFT算法发现火焰图像的多尺度特征,确定火焰极值点并进行特征匹配,有效识别火焰尖角以提高侦测的有效性。将分形理论的分数维作为火焰的特征加以使用。由于通常情况下火焰是异常值,一类分类器具有代价低、特征易获取、精度高等诸多优点,因此使用一类分类器完成火焰识别。实验证明,该研究不仅在近距离光照强的条件下具有良好的真阳性率和假阳性率,而且在光照弱的情况下具有较高的火焰发现率和较低的虚警率。

Abstract: Under undetermined and sophisticated environment,it is an unresolved puzzle for early flame detection based on image.Therefore,for the improvement in detection efficiency,this paper not only introduced the theory of histogram equalization to this field,but also brought in the SIFT algorithm to image process of determining multi-scale features of the flame pictures,identifying flame extreme point as well as feature matching.We regarded fractal dimension as one of flame features.Since flame is the anomalous value mostly and there are some advantages in one class classifier,such as low cost,easy to obtain features and high precision,one class classifier is used to identify the flame.The experiment proves in this research that there is excellent rate of true positive and false positive under the circumstances of close quarters and bright light,in addition,there is high detection rate of flame and low false alarm rate under the dim light condition.

Key words: SIFT algorithm,One class classifier,Fractal,Histogram equalization,Flame detection,Flame sharp angle

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