Title :
A Figure Extraction and Synthesis System by Learning Vector Quantization Neural Networks
Author :
Chang, Chuan-Yu ; Tsai, Zong-Yu ; Li, Chun-Hsi
Author_Institution :
Inst. of Comput. Sci. & Inf. Eng., Nat. Yunlin Univ. of Sci. & Technol., Douliou
Abstract :
Extracting complete figures from videos with complicated environments is difficult. A new figure extraction and synthesis system with capability of extracting figures from consecutive frames in a messy environment is proposed in this paper. A figure template is constructed based on the face detection results and some image processing techniques. Figural and non-figural features are extracted from the figure images. By means of these features, a learning vector quantization neural network (LVQNN) is applied to classify the uncertain regions into figural and non-figural objects. The extracted figure can be further synthesized into an optional cinestrip. Experimental results showed the proposed method successfully extract the figure object from a complex background environment.
Keywords :
feature extraction; image coding; learning (artificial intelligence); neural nets; vector quantisation; face detection; figure extraction; figure synthesis system; image processing techniques; learning vector quantization neural network; Bismuth; Computer science; Data mining; Discrete cosine transforms; Face detection; Image processing; Network synthesis; Neural networks; Vector quantization; Videos;
Conference_Titel :
Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on
Conference_Location :
Dalian, Liaoning
Print_ISBN :
978-0-7695-3161-8
Electronic_ISBN :
978-0-7695-3161-8
DOI :
10.1109/ICICIC.2008.29