A Novel Full Reference-Image Quality Assessment (FR-IQA) for Adaptive Visual Perception Improvement

Narsaiah, D; Reddy, Rami; Kokkula, Aruna; Kumar, P Anil; Karthik, A.

doi:10.1109/icict50816.2021.9358610

Cited by 4 publications

(4 citation statements)

References 14 publications

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“…It is frequently used in classification problems. Each data item is defined as a point in n-dimensional space in the SVM approach, with the value of each feature being the value of a single coordinate and simply the coordinates of a given observation [20], [22]. The SVM classifier has the advantage of discriminating between the two classes (hyperplane and line) the best.…”

Section: Support Vector Machine (Svm)mentioning

confidence: 99%

“…Then, all of these trees were run in parallel, and the final severity prediction of a road accident was calculated by averaging the predictions from all of the DTs. The number of trees, the maximum number of characteristics evaluated to divide a node, and the minimum number of leaves necessary to separate an internal node are three key criteria for enhancing RF prediction accuracy [20], [22], [29], [31], [34].…”

Section: Random Forest (Rf)mentioning

confidence: 99%

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Intelligent Model for Avoiding Road Accidents Using Artificial Neural Network

Kushwaha,

M.S. Abirami

2023

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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Accidents typically occurred on roads, resulting in significant societal losses. Road accidents are a worldwide issue that result in the loss of precious human lives and property. The purpose of this paper is to create an intelligent system-based on Machine Learning model for avoiding road accidents, as well as a system that effectively reduces road accidents severities. The Artificial Neural Network (ANN) algorithm, along with others such as Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Nave Bayes (NB), Stochastic Gradient Descent (SGD), Random Forest (RF), Gradient Boosting (GB), and AdaBoost, is used to create an intelligence system. Many driving collaborator procedures, installed in a few vehicles, assist drivers in avoiding vehicle crashes by providing early cautioning messages. The intelligence road crash avoidance system model is built on dataset of 29 columns and 1048575 rows. Preprocessing, feature selection, and feature extraction performed with the help of heat map and correlation matrix are used to select features. Linear Discriminant Analysis (LDA) is used for feature extraction. The testing dataset revealed that the proposed ANN method outperforms other algorithms with an accuracy of 0.856. Intelligent systems aid in the prevention of traffic accidents, which aids police officers and researchers in developing new policies.

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Section: Support Vector Machine (Svm)mentioning

confidence: 99%

Section: Random Forest (Rf)mentioning

confidence: 99%

Intelligent Model for Avoiding Road Accidents Using Artificial Neural Network

Kushwaha,

M.S. Abirami

2023

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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“…The measures for the objective Video Quality Assessment (VQA,) are studied from the measurements of the Image Quality Assessment (IQA). Since this research employs a controlled environment, the FR-IQA [19] is used. In FR-IQA algorithms, complete reference image information is needed to predict the quality of degraded or distorted images; these algorithms generally perform pixel disparity measurements between reference and distorted images.…”

Section: B Objective Estimationmentioning

confidence: 99%

Construction of a Video Transmission Scenario in Software-Defined Networks for QoE Estimation

2022

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The services supported by data networks have become widespread, so the architectures of the new data networks are service-oriented. They are endowed with intelligence, flexibility, and programmability. The preceding is with the aim of providing acceptability by users. Thus, this paper presents the construction of a video transmission scenario over a software-defined network (SDN, Software-Defined Networking) using free software and modifying its behavior with background traffic, on which the Quality of Experience (QoE) is estimated. Subjective and objective metrics were used for the QoE estimation. For the first one, the Mean Opinion Score (MOS) was used, while the second one was studied with the Full Reference Image Quality Assessment (FR-IQA). Finally, a correlation between the two types of metrics was proposed.

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“…However, reference images are often difficult or impossible to obtain, which limits the application of FR-IQA. Recently, several quality assessment methods based on FR-IQA are proposed [12,13] to improve the accuracy of assessment. Although these methods improve the performance of assessment, the limitations of the FR method remain.…”

Section: Introductionmentioning

confidence: 99%

Quality assessment for inspection images of power lines based on spatial and sharpness evaluation

Liu

Jin

Jiang

et al. 2021

IET Image Processing

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Digital imaging and image-processing techniques have revolutionized the way of power line inspection in recent years. Massive images are captured and utilized for further processing to maintain the reliability, safety, and sustainability of power transmission. For power line inspection, the component region in the delivered images is required to be centered, large, and clear enough. In this paper, a component-oriented image quality assessment method is proposed to automatically predict image quality according to the demand of power line inspection. The proposed method considers two factors: spatial characteristic evaluation and sharpness evaluation. The spatial characteristic evaluation utilizes YOLOv3 to evaluate whether the component region is sufficiently centered and large, which enables the observer to quickly find the target. The sharpness evaluation employs ResNet to evaluate the clarity of component and makes the condition monitoring more accurately. For final quality assessment, a multi-stage filtering strategy is presented to aggregate these two factors and obtain high quality inspection images. The experimental results indicate that the high-quality images can be accurately identified to satisfy the requirements of power line inspection. The proposed quality assessment method enhances the efficiency for further data analysis of aerial images.

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A Novel Full Reference-Image Quality Assessment (FR-IQA) for Adaptive Visual Perception Improvement

Cited by 4 publications

References 14 publications

Intelligent Model for Avoiding Road Accidents Using Artificial Neural Network

Intelligent Model for Avoiding Road Accidents Using Artificial Neural Network

Construction of a Video Transmission Scenario in Software-Defined Networks for QoE Estimation

Quality assessment for inspection images of power lines based on spatial and sharpness evaluation

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