Modification of Lab color model for minimizing blue-green illumination of underwater vision system

2018 ◽  
Author(s):  
Ahmad Shahrizan Abdul Ghani ◽  
Ahmad Fakhri Ab. Nasir ◽  
Muhammad Aizzat Zakaria ◽  
Ahmad Najmuddin Ibrahim
Keyword(s):  
Vision System ◽  
Color Model ◽  
Underwater Vision ◽  
Lab Color Model

Optical Sources Optimization for 3D Reconstruction Based on Underwater Vision System

2019 ◽  
Author(s):  
Tengyue Li ◽  
Bo He ◽  
Shizhe Tan ◽  
Chen Feng ◽  
Shuai Guo ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Vision System ◽  
Underwater Vision

scholarly journals The Application of Computer Image Analysis Based on Textural Features for the Identification of Barley Kernels Infected with Fungi of the Genus Fusarium

2018 ◽  
Vol 22 (3) ◽  
pp. 49-56 ◽  
Author(s):  
Ewa Ropelewska
Keyword(s):  
Image Analysis ◽  
Selection Method ◽  
Color Model ◽  
Textural Features ◽  
Discriminative Power ◽  
Selection Methods ◽  
Computer Image Analysis ◽  
Genus Fusarium ◽  
Color Models ◽  
Lab Color Model

AbstractThe aim of this study was to develop discrimination models based on textural features for the identification of barley kernels infected with fungi of the genus Fusarium and healthy kernels. Infected barley kernels with altered shape and discoloration and healthy barley kernels were scanned. Textures were computed using MaZda software. The kernels were classified as infected and healthy with the use of the WEKA application. In the case of RGB, Lab and XYZ color models, the classification accuracies based on 10 selected textures with the highest discriminative power ranged from 95 to 100%. The lowest result (95%) was noted in XYZ color model and Multi Class Classifier for the textures selected using the Ranker method and the OneR attribute evaluator. Selected classifiers were characterized by 100% accuracy in the case of all color models and selection methods. The highest number of 100% results was obtained for the Lab color model with Naive Bayes, LDA, IBk, Multi Class Classifier and J48 classifiers in the Best First selection method with the CFS subset evaluator.

scholarly journals Silhouette index for determining optimal k-means clustering on images in different color models

2018 ◽  
Vol 7 (2.14) ◽  
pp. 105 ◽  
Author(s):  
Abd Rasid Mamat ◽  
Fatma Susilawati Mohamed ◽  
Mohamad Afendee Mohamed ◽  
Norkhairani Mohd Rawi ◽  
Mohd Isa Awang
Keyword(s):  
Image Processing ◽  
Color Model ◽  
Cluster Validation ◽  
Validation Process ◽  
Color Models ◽  
Silhouette Index ◽  
Hsv Color Model ◽  
Different Color ◽  
Lab Color Model ◽  
Cie Lab

Clustering process is an essential part of the image processing. Its aim to group the data according to having the same attributes or similarities of the images. Consequently, determining the number of the optimum clusters or the best (well-clustered) for the image in different color models is very crucial. This is because the cluster validation is fundamental in the process of clustering and it reflects the split between clusters. In this study, the k-means algorithm was used on three colors model: CIE Lab, RGB and HSV and the clustering process made up to k clusters. Next, the Silhouette Index (SI) is used to the cluster validation process, and this value is range between 0 to 1 and the greater value of SI illustrates the best of cluster separation. The results from several experiments show that the best cluster separation occurs when k=2 and the value of average SI is inversely proportional to the number of k cluster for all color model. The result shows in HSV color model the average SI decreased 14.11% from k = 2 to k = 8, 11.1% in HSV color model and 16.7% in CIE Lab color model. Comparisons are also made for the three color models and generally the best cluster separation is found within HSV, followed by the RGB and CIE Lab color models.  

scholarly journals ROV-based Underwater Vision System for Intelligent Fish Ethology Research

10.5772/56800 ◽  
2013 ◽  
Vol 10 (9) ◽  
pp. 326 ◽  
Author(s):  
Rui Nian ◽  
Bo He ◽  
Jia Yu ◽  
Zhenmin Bao ◽  
Yangfan Wang
Keyword(s):  
Vision System ◽  
Underwater Vision

scholarly journals Using the pixel information value parameter in an entropy image analysis criterion

2018 ◽  
pp. 67-72
Author(s):  
R. Kvyetnyy ◽  
A. Olesenko
Keyword(s):  
Image Analysis ◽  
Standard Test ◽  
Information Value ◽  
Color Model ◽  
Adjacent Pixel ◽  
Lab Color Model ◽  
Entropy Criterion ◽  
Modified Entropy

The work is devoted to the development and research of the entropy criterion of image analysis on its corresponding to the method of RLE-compression. The Lab color model and the CIEDE1976 color estimation metric have been analyzed. The pixel information importance parameter has been introduced, which is based on the above described metric and allows us to estimate the importance of the adjacent pixel taking into consideration the information it introduces in relation to the previous pixel. The modified entropy image analysis criterion has been developed taking into account the pixel’s information importance parameter. The adequacy of the proposed criterion has been checked on the sample of standard test images and the feasibility of its use has been proved.

scholarly journals Исследование изменений в спектре поглощения современных хлоринсодержащих препаратов для фотодинамической терапии и метиленового синего в результате воздействия светодиодного излучения с длиной волны 656± 10 nm

2020 ◽  
Vol 129 (7) ◽  
pp. 972
Author(s):  
А.В. Беликов ◽  
Ю.В. Семяшкина ◽  
С.Н. Смирнов ◽  
А.Д. Тавалинская
Keyword(s):  
Methylene Blue ◽  
Aqueous Solutions ◽  
Absorption Spectra ◽  
Exposure Time ◽  
Spectral Range ◽  
Color Model ◽  
Absorption Bands ◽  
Lab Color Model ◽  
Cie Lab ◽  
The Impact

The changes in absorption spectra of aqueous solutions of modern chlorine-containing photosensitizing preparations "Revixan" (Areal, Russia) and "Chloderm" (Chloderm, Russia) depending on the intensity of LED radiation with wavelength of 656 ± 10 nm and exposure time were studied in spectral range 600-700 nm. The parameters of the CIE Lab color model of the image of "Revixan" aqueous solution before and after LED exposure were investigated. The changes in absorption spectra of aqueous solutions of methylene blue with different initial concentrations arising after exposure to LED radiation with intensity of 180 ± 20 mW/cm2 were studied in the spectral range 400-900 nm. It was shown that the impact of LED radiation changes the absorption spectra of the studied preparations and increases the parameter L (lightness) of the CIE Lab color model for "Revixan". An increase in the LED radiation intensity and exposure time leads to a decrease in absorption for "Revixan" and "Chloderm" in spectral range 600-700 nm and to a shift of the peaks of absorption bands lying in this range towards a longer wavelength. The impact of LED radiation on aqueous solutions of methylene blue leads to a decrease in their absorption in spectral range 400-900 nm.

Active pulse underwater vision system

2020 ◽  
Author(s):  
Yuri Gruzevich ◽  
Mariia Khodakovskaia ◽  
Vitalii Khodakovskii
Keyword(s):  
Vision System ◽  
Underwater Vision

scholarly journals Development of an Artificial Vision System for Underwater Vehicles

Proceedings ◽  
2019 ◽  
Vol 21 (1) ◽  
pp. 1
Author(s):  
Sanmartín ◽  
Briceño
Keyword(s):  
Operating System ◽  
Navigation System ◽  
Vision System ◽  
Underwater Vehicles ◽  
Artificial Vision ◽  
Optical Systems ◽  
Main Obstacle ◽  
Robot Operating System ◽  
Underwater Vision

Beyond certain depth there is no light, supposing the main obstacle in the use of optical systems beneath the water. Therefore, the underwater vision system developed is composed of a set of underwater lights which allow the system to work properly and the cameras. These are integrated with the navigation system through the Robot Operating System (ROS) framework, which handles the acquisition and processing of information to be used as support for the navigation and which is also essential for its use in reconnaissance missions.

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