Title :
Novel Contour Vectorization Using Holistic Feature of Object
Author :
Lu Qichao ; Yang Guang ; Gao Feng
Author_Institution :
Sch. of Comput. Sci. & Eng., BeiHang Univ., Beijing, China
Abstract :
In this paper, a novel contour vectorization approach based on holistic feature of object is proposed, which aims at avoiding segmenting an entire contour of target into some discrete sets of curves. This method consists of two steps:(1) Digitize pixel-based contour into vectors or arcs referring to holistic feature of object, and the contour trend used in the implementation of vectorization is defined here;(2)Approximate vectors and arcs to regular figures, including various postprocessing treatments. Innovative and significant features of this approach includes: preservation of original contour shape; low-loss of performance in noisy environments; linear time complexity and neglectable space complexity. The experimental results obtained confirm the validity of the proposed approach.
Keywords :
computational complexity; computer vision; feature extraction; object detection; contour vectorization; discrete set; holistic object feature; linear time complexity; noisy environment; pixel based contour; postprocessing treatment; regular figure; space complexity; Complexity theory; Feature extraction; Humans; Noise; Noise measurement; Pixel; Robustness;
Conference_Titel :
Pattern Recognition (CCPR), 2010 Chinese Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-7209-3
Electronic_ISBN :
978-1-4244-7210-9
DOI :
10.1109/CCPR.2010.5659170