On the Removal of Shadows from Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shadow Removal from a Single Image
ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 02
Shadow identification and classification using invariant color models
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
ISCGAV'08 Proceedings of the 8th conference on Signal processing, computational geometry and artificial vision
Shadow detection: A survey and comparative evaluation of recent methods
Pattern Recognition
A survey of cast shadow detection algorithms
Pattern Recognition Letters
Contour detection based on nonclassical receptive field inhibition
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
The timing of the grape harvest has a strong impact on wine quality. A recent line of studies proposes visual seed inspection by a trained expert to determine Phenolic Maturity. In this paper a method is presented to estimate Grape Phenolic Maturity based on seed images. The acquired images present problems such as shadows, highlights and low contrast. Two classes of seed are defined (mature and immature) by the expert (enologist) involved in the research. The method consists of three stages: segmentation, feature extraction and classification. Segmentation was performed by a hybrid method combining supervised and unsupervised learning, feature extraction by the Sequential Forward Selection algorithm, and classification by a Simple Perceptron. The results for each stage are presented. The method as a whole proved to be simple and effective in the classification of seeds. Therefore, it is possible to visualize the implementation of the method in real conditions.