首页    期刊浏览 2024年12月12日 星期四
登录注册

文章基本信息

  • 标题:Hybrid Technique for Human Face Emotion Detection
  • 本地全文:下载
  • 作者:Renu Nagpal ; Pooja Nagpal ; Sumeet Kaur
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2010
  • 卷号:1
  • 期号:6
  • DOI:10.14569/IJACSA.2010.010615
  • 出版社:Science and Information Society (SAI)
  • 摘要:This paper presents a novel approach for the detection of emotions using the cascading of Mutation Bacteria Foraging optimization and Adaptive Median Filter in highly corrupted noisy environment. The approach involves removal of noise from the image by the combination of MBFO & AMF and then detects local, global and statistical feature form the image. The Bacterial Foraging Optimization Algorithm (BFOA), as it is called now, is currently gaining popularity in the community of researchers, for its effectiveness in solving certain difficult real-world optimization problems. Our results so far show the approach to have a promising success rate. An automatic system for the recognition of facial expressions is based on a representation of the expression, learned from a training set of pre-selected meaningful features. However, in reality the noises that may embed into an image document will affect the performance of face recognition algorithms. As a first we investigate the emotionally intelligent computers which can perceive human emotions. In this research paper four emotions namely anger, fear, happiness along with neutral is tested from database in noisy environment of salt and pepper. Very high recognition rate has been achieved for all emotions along with neutral on the training dataset as well as user defined dataset. The proposed method uses cascading of MBFO & AMF for the removal of noise and Neural Networks by which emotions are classified.
  • 关键词:thesai; IJACSA; thesai.org; journal; IJACSA papers; biomertics;adaptive median filter; bacteria foraging optimization;feature detection;facial expression
国家哲学社会科学文献中心版权所有