Image binarization under non-uniform illumination based on gray-intensity wave equalization

2013 ◽  
Author(s):  
Wei Wei
Keyword(s):  
Image Binarization ◽  
Uniform Illumination ◽  
Gray Intensity ◽  
Intensity Wave

scholarly journals Damaged solar cell detection based on gray-intensity wave transformation

2011 ◽  
Vol 15 ◽  
pp. 3808-3813 ◽  
Author(s):  
Xuanjing Shen ◽  
Wei Wei ◽  
Jianwu Long ◽  
Qingji Qian
Keyword(s):  
Solar Cell ◽  
Wave Transformation ◽  
Cell Detection ◽  
Gray Intensity ◽  
Intensity Wave

Wave Equalization - A New Image Enhancement Method for Gray Image Binarization under Uneven Illumination

2014 ◽  
Vol 631-632 ◽  
pp. 470-473
Author(s):  
Wei Wei
Keyword(s):  
Image Enhancement ◽  
Image Binarization ◽  
Uniform Illumination ◽  
Excellent Performance ◽  
Gray Image ◽  
3D Terrain ◽  
Enhancement Method ◽  
Pca Algorithm

The gray image can be viewed as a 3D terrain consisting of intensity waves. The Wave Equalization introduced in the paper is to weaken the influence of uneven illumination on the gray image binarization. The 2D wave is decomposed into several 1D waves corresponding to different directions for 1D equalization. Then PCA algorithm is used to compress all 1D results to the final image with uniform illumination. The extensive experiments in the paper had proved that our method has excellent performance and adaptability for various uneven illumination environments.

Dark Channel Applied for Reduction of the Effects of Non-uniform Illumination in Image Binarization

2019 ◽  
Vol 23 (2) ◽  
Author(s):  
Sebastián Salazar Colores ◽  
Mariano Garduño Aparicio ◽  
Eduardo Ulises Moya Sánchez ◽  
Claudia Victoria Lopez Torres ◽  
Juan Manuel Ramos Arreguín
Keyword(s):  
Image Binarization ◽  
Uniform Illumination ◽  
Dark Channel

scholarly journals Sugeno integral generalization applied to improve adaptive image binarization

2021 ◽  
Vol 68 ◽  
pp. 37-45
Author(s):  
Francesco Bardozzo ◽  
Borja De La Osa ◽  
Ľubomíra Horanská ◽  
Javier Fumanal-Idocin ◽  
Mattia delli Priscoli ◽  
...  
Keyword(s):  
Image Binarization ◽  
Sugeno Integral

Classification and Recognition of Plant Leaf Based on Neural Networks

2011 ◽  
Vol 464 ◽  
pp. 38-42 ◽  
Author(s):  
Ping Ye ◽  
Gui Rong Weng
Keyword(s):  
Neural Networks ◽  
Fractal Dimension ◽  
Recognition Rate ◽  
Image Binarization ◽  
Characteristic Parameters ◽  
Moment Invariant ◽  
Plant Leaf ◽  
The Neural Networks ◽  
Novel Method ◽  
The Moment

This paper proposed a novel method for leaf classification and recognition. In the method, the moment invariant and fractal dimension were regarded as the characteristic parameters of the plant leaf. In order to extract the representative characteristic parameters, pretreatment of the leaf images, including RGB-gray converting, image binarization and leafstalk removing. The extracted leaf characteristic parameters were further utilized as training sets to train the neural networks. The proposed method was proved effectively to reach a recognition rate about 92% for most of the testing leaf samples

scholarly journals Camera-based localization microscopy optimized with calibrated structured illumination

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Martin Schmidt ◽  
Adam C. Hundahl ◽  
Henrik Flyvbjerg ◽  
Rodolphe Marie ◽  
Kim I. Mortensen
Keyword(s):  
Data Analysis ◽  
Super Resolution ◽  
Wide Field ◽  
Structured Illumination ◽  
Uniform Illumination ◽  
Localization Microscopy ◽  
Localization And Tracking ◽  
Field Imaging ◽  
Wide Field Imaging ◽  
Localization Information

AbstractUntil very recently, super-resolution localization and tracking of fluorescent particles used camera-based wide-field imaging with uniform illumination. Then it was demonstrated that structured illuminations encode additional localization information in images. The first demonstration of this uses scanning and hence suffers from limited throughput. This limitation was mitigated by fusing camera-based localization with wide-field structured illumination. Current implementations, however, use effectively only half the localization information that they encode in images. Here we demonstrate how all of this information may be exploited by careful calibration of the structured illumination. Our approach achieves maximal resolution for given structured illumination, has a simple data analysis, and applies to any structured illumination in principle. We demonstrate this with an only slightly modified wide-field microscope. Our protocol should boost the emerging field of high-precision localization with structured illumination.

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