Shadow Detection Using Double-Threshold Pulse Coupled Neural Networks
A novel double-threshold pulse coupled neural networks (DTPCNN) is proposed and applied to shadow detection. It attempts to reduce the false detection of shadows in a single image where the hue and brightness of some non-shadow regions are similar to or even lower than those of shadows. Shadows whos...
Saved in:
Main Authors: | Sun, Wei, Ji, Jing, Jiang, Xudong |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2016
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/80620 http://hdl.handle.net/10220/40656 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Simple global thresholding neural network for shadow detection
by: Li, Guiyuan, et al.
Published: (2022) -
STUDY OF DAMAGE THRESHOLD OF SUBSTRATE IN LASER CLEANING PROCESS
by: LEK AIK WEE
Published: (2020) -
A dynamic conditional random field model for foreground and shadow segmentation
by: Wang, Y., et al.
Published: (2013) -
DANI-Net: uncalibrated photometric stereo by differentiable shadow handling, anisotropic reflectance modeling, and neural inverse rendering
by: Li, Zongrui, et al.
Published: (2023) -
Preserving shadows: Engaging digital-material in shadow play
by: Arabit, Maysa Salonga
Published: (2018)