Name
Abstract | ||
|---|---|---|
Analyzing an image means extracting a number of relevant features for describing, meaningfully and concisely, image content. Usually, the selection of the features to be extracted depends on the image based task that has to be performed. This problem-dependency has caused the flourish of number and number of features in the literature, with a substantial disorganization of their introduction and definition. The idea behind the work reported in this paper is to make a step towards the systematization of the image feature domain by defining an ontological model, in which features and other concepts, relevant to feature definition and computation, are formally defined and catalogued. To this end, the Image Feature Ontology has been defined and is herein described. Such an ontology has the peculiarity of cataloguing features, modelling the image analysis domain and being integrated with a library of image processing algorithms, thus supplying functionalities for supporting feature selection and computation. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-32436-9_2 | MUSCLE |
Keywords | Field | DocType |
feature selection,relevant feature,algorithms integration,image processing algorithm,image feature domain,image content,cataloguing feature,image feature ontology,substantial disorganization,ontological model,image analysis domain | Data mining,Ontology,Feature detection (computer vision),Feature selection,Computer science,Artificial intelligence,Ontology (information science),Automatic image annotation,Pattern recognition,Information retrieval,Feature (computer vision),Feature extraction,Digital image processing | Conference |
Citations | PageRank | References |
1 | 0.48 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sara Colantonio | 1 | 58 | 14.24 |
| Massimo Martinelli | 2 | 47 | 10.09 |
| Ovidio Salvetti | 3 | 168 | 46.26 |