FaceSeg: automatic face segmentation for real-time video
IEEE Transactions on Multimedia
Automatic segmentation of focused objects from images with low depth of field
Pattern Recognition Letters
Automatic moving object segmentation from video sequences using alternate flashing system
EURASIP Journal on Advances in Signal Processing - Special issue on video analysis for human behavior understanding
Automatic body segmentation with graph cut and self-adaptive initialization level set (SAILS)
Journal of Visual Communication and Image Representation
Segmenting focused objects based on the Amplitude Decomposition Model
Pattern Recognition Letters
Directional high-pass filter for blurry image analysis
Image Communication
Image matting for fusion of multi-focus images in dynamic scenes
Information Fusion
Short Communication: A rectilinear Gaussian model for estimating straight-line parameters
Journal of Visual Communication and Image Representation
| Hi-index | 0.00 |
In this paper, a novel segmentation algorithm based on matting model is proposed to extract the focused objects in low depth-of-field (DoF) video images. The proposed algorithm is fully automatic and can be used to partition the video image into focused objects and defocused background. This method consists of three stages. The first stage is to generate a saliency map of the input image by the reblurring model. In the second stage, bilateral and morphological filtering are employed to smooth and accentuate the salient regions. Then a trimap with three regions is calculated by an adaptive thresholding method. The third stage involves the proposed adaptive error control matting scheme to extract the boundaries of the focused objects accurately. Experimental evaluation on test sequences shows that the proposed method is capable of segmenting the focused region effectively and accurately.