| Autor: |
Venugopal Gundimeda, N. T. Naresh Babu, Ratan S. Murali, Rajkumar Joseph |
| Rok vydání: |
2018 |
| Předmět: |
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| Zdroj: |
Advances in Intelligent Systems and Computing ISBN: 9789811315794 |
| DOI: |
10.1007/978-981-13-1580-0_1 |
| Popis: |
Retailers need good-quality product images with clear background on their Web sites. Most of these product images captured have diverse backgrounds, posing a challenge to separate the foreground from the background along with the enhancement of the product image. Currently, most of these activities are done manually. Our study proposes a computer vision (CV)- and machine learning (ML)-based approach to separate foreground (FG) and background (BG) from retail product images and enhance them. This automated process of BG/FG extraction involves two steps. A neural network (NN) classifier to identify if the BG has a monocolor gradient or not, followed by the separation of FG from BG and enhancement applied on the FG from the input image. Our results show 91% accuracy for BG/FG extraction and identifying the product region of interest (ROI). |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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