Nowadays, retrieving a person identity using a photograph from the face image database is a crucial job especially in police investigations. Unfortunately in many cases,the photo image of a suspect is not available. Only a face sketch drawing based on the recollection of an eyewitness is available. Usually, there are two kind of face sketches employed in police investigations i.e. halftone face sketches. In this paper, we propose a modified line gradient method called Maximum Line Gradient Method to detect multiple features from halftone face sketches by using simultaneously moving shapes and landmarks. Our proposed method is divided into four stages: training, create image gradient, shape initialization, and multiple features detection processes. The last stage is started by searching the maximum line gradient value between two landmarks. Thus, by using the Similarity Transformation Equation, the set of landmarks (shape) will be simultaneously moved. The position of new landmark is enhanced by using simultaneously landmark movements on each shape. In the experiment, we employ 50 halftone face sketches which being examined by using 7 features with 38 landmarks. Our propose method demonstrates that the detection accuracy is 92.16%.

Original languageEnglish
Title of host publicationSoCPaR 2009 - Soft Computing and Pattern Recognition
Number of pages6
Publication statusPublished - 2009
EventInternational Conference on Soft Computing and Pattern Recognition, SoCPaR 2009 - Malacca, Malaysia
Duration: 4 Dec 20097 Dec 2009

Publication series

NameSoCPaR 2009 - Soft Computing and Pattern Recognition


ConferenceInternational Conference on Soft Computing and Pattern Recognition, SoCPaR 2009


  • Active shape model
  • Face sketch
  • Feature detection
  • Line gradient
  • Police investigations


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