Name
Abstract | ||
|---|---|---|
Human visual system always focuses on the salient region of an image. From that region the salient features are obtained and can be collected by generating the saliency map. Natural statistics measures are used to measure the saliency from data collection of natural images. ICA filters are used to generate the saliency map that can blur the image. We have improved it by using different techniques like edge detection and morphological operations. By applying these algorithms we have successfully reduced the blur in images. That makes the salient objects more prominent by sharpening the edges. Proposed method is also compared with the state-of-the-art method like Achanta model. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-981-10-4154-9_14 | Lecture Notes in Electrical Engineering |
Keywords | Field | DocType |
Saliency,Edge detection,Morphological image processing,AUC score | Sharpening,Data collection,Computer vision,Object detection,Kadir–Brady saliency detector,Salience (neuroscience),Human visual system model,Edge detection,Computer science,Artificial intelligence,Salient | Conference |
Volume | ISSN | Citations |
424 | 1876-1100 | 1 |
PageRank | References | Authors |
0.35 | 14 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rehan Yousaf | 1 | 1 | 0.35 |
| Saad Rehman | 2 | 18 | 9.09 |
| Hassan Dawood | 3 | 67 | 14.45 |
| Ping Guo | 4 | 601 | 85.05 |
| Zahid Mehmood | 5 | 45 | 7.03 |
| Shoaib Azam | 6 | 7 | 3.09 |
| Abdullah Aman Khan | 7 | 1 | 0.35 |