Name
Title | ||
|---|---|---|
Change Detection and Object Segmentation: A Histogram of Features-Based Energy Minimization Approach |
Abstract | ||
|---|---|---|
We consider here a change detection problem: to find regions of change on a test image with respect to a reference image. Unlike the state-of-the-art change detection and background subtraction algorithms that compute only local (pixel location-based) changes, we propose to minimize a novel region-based energy functional based on Bhattacharya coefficient involving histograms of image features. The optimization of the proposed energy functional simply consists of two very efficient searches if a crude segmentation such as a bounding box around the region of change is sufficient. Also, it allows variational optimization via level set-based curve evolution for supervised binary image labeling. The framework is demonstrated to cope well with considerable camera motion and shifts of objects between the test and the reference images. We illustrate encouraging results on finding bounding box around abnormality from brain MRI, object detection for maritime surveillance, and segmenting oil-sand particles from conveyor belt images. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICVGIP.2008.52 | ICVGIP |
Keywords | Field | DocType |
novel region-based energy,supervised binary image,proposed energy,state-of-the-art change detection,object detection,image feature,object segmentation,features-based energy minimization approach,change detection problem,reference image,test image,change detection,conveyor belt image,pixel,minimisation,energy minimization,magnetic resonance imaging,background subtraction,labeling,level set,oil sand,binary image,image segmentation,probability density function,image features,motion estimation,histograms,feature extraction | Background subtraction,Object detection,Computer vision,Change detection,Pattern recognition,Computer science,Feature (computer vision),Binary image,Image segmentation,Artificial intelligence,Standard test image,Minimum bounding box | Conference |
Citations | PageRank | References |
1 | 0.41 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ray Nilanjan | 1 | 541 | 55.39 |
| Baidya Nath Saha | 2 | 59 | 7.95 |
| Hong Zhang | 3 | 582 | 74.33 |