Name
Abstract | ||
|---|---|---|
This paper proposes a new representation for color texture using a set of multiscale illuminant invariant features. The approach was specifically developed to investigate the feasibility of using machine vision to automatically monitor populations of animal species in the Amazon Forest. The approach uses a combination of Finlayson's (1996) color angle idea and Gabor multichannel filters. Using a database of color textures from species of Amazonian monkey, and also a previously published reference database of color regions, we show that the approach performs better than methods based on color angles or Gabor filters alone. The Monkey database was compiled from texture segments extracted from a video of the Amazon Forest using a spatial-temporal segmentation algorithm. The approach is evaluated by applying two classification tests in order to measure the quality of the recognition features: root mean square (RMS) analysis and receiver operating characteristic (ROC) analysis |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1109/ICIP.2001.959182 | Image Processing, 2001. Proceedings. 2001 International Conference |
Keywords | Field | DocType |
channel bank filters,computer vision,feature extraction,filtering theory,image classification,image colour analysis,image recognition,image representation,image texture,receivers,two-dimensional digital filters,video signal processing,zoology,2D Gabor filters,Amazon Forest,Amazonian monkey,Gabor multichannel filters,Monkey database,RMS analysis,ROC analysis,animal species,classification system,classification tests,color angle,color regions,color texture representation,color textures database,image recognition,machine vision,multiscale color invariants,multiscale illuminant invariant features,multiscale texture invariants,population monitoring,receiver operating characteristic,reference database,root mean square analysis,spatial-temporal segmentation algorithm,texture segments,video | Computer vision,Pattern recognition,Machine vision,Computer science,Segmentation,Image texture,Feature extraction,Artificial intelligence,Root mean square,Standard illuminant,Invariant (mathematics),Contextual image classification | Conference |
Volume | ISSN | ISBN |
1 | 1522-4880 | 0-7803-6725-1 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Juliana F. Camapum Wanderley | 1 | 0 | 0.34 |
| Mark Fisher | 2 | 163 | 18.49 |