Object Contour Extraction Using Adaptive B-Snake Model
Journal of Mathematical Imaging and Vision
Oriented connectivity-based method for segmenting solar loops
Pattern Recognition
Dynamic B-snake model for complex objects segmentation
Image and Vision Computing
Human tracking: a state-of-art survey
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
Linear fuzzy space based road lane model and detection
Knowledge-Based Systems
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In this paper, we proposed a new B-snake based lane detection algorithm. Compared with other lane models, the B-snake based lane model is able to describe a wider range of lane structures, since B-spline can form any arbitrary shape by a set of control points. The problems of detecting both sides of lane markings (or boundaries) have been formulated here as the problem of detecting the mid-line of the lane, by using the knowledge of the perspective parallel lines. A robust algorithm called CHEVP is presented for providing a good initial position for the B-snake. Furthermore, a minimum energy method by MMSE (Minimum Mean Square Energy) is suggested to determine the control points of the B-snake model by the overall image forces on two sides of lane. Experimental results show that the proposed method is robust against noise, shadows, and illumination variations in the captured road images, and also applicable to both the marked and the unmarked roads, and the dash and the solid paint line roads.