New effective techniques for automatic detection and classification of external olive fruits defects based on image processing techniques

DOI10.1007/S11045-018-0573-5zbMath1441.94011OpenAlexW2794878045MaRDI QIDQ2415843

Nashat M. Hussain Hassan, Ahmed A. Nashat

Publication date: 23 May 2019

Published in: Multidimensional Systems and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11045-018-0573-5

zbMATH Keywords

features extractionimage segmentation techniquesartificial vision techniquesimage convolution techniquesolive fruit classification techniques

Mathematics Subject Classification ID

Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Detection theory in information and communication theory (94A13)

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Cites Work

• Unnamed Item
• Periodic wavelet descriptor of plant leaf and its application in botany
• Wavelet-based spectral descriptors for detection of damage in sunflower seeds
• Automatic segmentation and classification of olive fruits batches based on discrete wavelet transform and visual perceptual texture features
• LSDT: Latent Sparse Domain Transfer Learning for Visual Adaptation
• Median Robust Extended Local Binary Pattern for Texture Classification
• Robust Visual Knowledge Transfer via Extreme Learning Machine-Based Domain Adaptation
• THE NORMALIZED WAVELET DESCRIPTOR FOR SHAPE RETRIEVAL

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