Adaptive image enhancement algorithm based on the model of surface roughness detection system

Tian, Jie; Yin, Xijie

doi:10.1186/s13640-018-0343-1

Cited by 7 publications

(3 citation statements)

References 18 publications

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“…The roughness detection method is a non-linear approach which analysis the surface by imaging technology and de-noises the image pixels. The pixel de-noising is performed by a masking operator, which amplifies the image pixels [43]. Aneela Sabir et al present a segmented-based image defogging method for image enhancement by adjusting the pixel's colour, contrast, and visibility.…”

Section: Wavelet Based Methodsmentioning

confidence: 99%

An Astute Automaton Model for Objects Extraction Using Outer Totality Cellular Automata (OTCA)

Sharma,

Basheer

et al. 2023

IEEE Access

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Object formation is imperative to the recent computer vision, pattern recognition, healthcare, and automation applications. The objects are generated from images by defining edges and the segmentation process. This article introduced a novel method, Outer Totality Cellular Automata (OTCA), for defining actual and continuous edges of the image objects. The OTCA analysis nearby 25 neighbourhood pixels of all the pixels and generate a unique and efficient threshold. The proposed method has three primary functions, i.e. vitality, rule mapping, and improved morphological functions. The key objectives are image smoothing, neighbourhood analysis, defining game of life rule, and edges smoothing. Notably, the proposed method aimed to segment different coloured images, i.e., RGB, HSV, and YUV. The proposed method also aimed to produce more truthful results on blurred, reflected, shaded night vision images. The experimental process demonstrates using standard open-source datasets and validated using image quality assessment parameters, i.e., entropy, PSNR, SSIM, and MSE. The results claim 3% − 12% more structural analogous, factual, and accurate than existing classical methods and recent searches.

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Section: Wavelet Based Methodsmentioning

confidence: 99%

An Astute Automaton Model for Objects Extraction Using Outer Totality Cellular Automata (OTCA)

Sharma,

Basheer

et al. 2023

IEEE Access

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“…The GMM includes modeling, expectationmaximization method, partitioning, and mapping, which is applied for low contrast images to achieve better quality images. The image enhancement techniques for denoising and contrast enlargement on low light images by Li et al [22] and for surface roughness detection system by Tian et al [23] are discussed in detail with performance metrics improvements.…”

Section: Related Workmentioning

confidence: 99%

Design and Analysis of Imaging Chip using High-Speed AXI-Interface for MPSOC Applications on FPGA Platform

Archana,

Reddy

2024

Wireless Pers Commun

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The recent innovations in real-time video and image enhancements are allowing much advancement in a wide range of diverse applications. These innovations and advancements provide a new hardware architecture which aims to improve the image visualization, processing speed, and complexity reduction in hardware. The imaging chip concept is introduced in this article to support the Multiprocessing system on chip (MPSoC) applications in real-time scenarios on a single chip. The imaging chip model is designed using high-speed interface protocol, which includes different image enhancement algorithms acts as a master model, Advanced Extensible Interface (AXI)-4 as an interface model, and dual-port memory as a slave model. The image enhancement algorithm includes mainly, Brightness control, contrast stretching, Adaptive median filtering (AMF), Edge-detection techniques, image Thresholding, and Image Histogram method. The AXI-4 provides a high-speed interface for communicating master and slave modules. The proposed model work based on the modes of the operation to process the enhanced image output in MPSoC. The design supports multiple masters and multiple slave modules with reconfigurable nature. The imaging chip is a module on the Xilinx ISE environment and implemented on Artix-7 FPGA, along with the performance metrics like chip Area, time, power, and memory utilization are analyzed with improvements. The model offers low latency and high throughput architecture for real-time Multimedia applications.

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“…A new strategy for adaptive image improvement is developed by analyzing the image characteristics of the adaptive images in [277]. Firstly, MSRDS segmentation of the base layer of the image.…”

Section: Surface Characteristics Measurement For Part's Surface Gener...mentioning

confidence: 99%

Surface Characteristics Measurement Using Computer Vision: A Review

Hashmi¹,

Mali²,

Meena³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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Computer vision provides image-based solutions to inspect and investigate the quality of the surface to be measured. For any components to execute their intended functions and operations, surface quality is considered equally significant to dimensional quality. Surface Roughness (Ra) is a widely recognized measure to evaluate and investigate the surface quality of machined parts. Various conventional methods and approaches to measure the surface roughness are not feasible and appropriate in industries claiming 100% inspection and examination because of the time and efforts involved in performing the measurement. However, Machine vision has emerged as the innovative approach to executing the surface roughness measurement. It can provide economic, automated, quick, and reliable solutions. This paper discusses the characterization of the surface texture of surfaces of traditional or non-traditional manufactured parts through a computer/machine vision approach and assessment of the surface characteristics, i.e., surface roughness, waviness, flatness, surface texture, etc., machine vision parameters. This paper will also discuss multiple machine vision techniques for different manufacturing processes to perform the surface characterization measurement.

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Adaptive image enhancement algorithm based on the model of surface roughness detection system

Cited by 7 publications

References 18 publications

An Astute Automaton Model for Objects Extraction Using Outer Totality Cellular Automata (OTCA)

An Astute Automaton Model for Objects Extraction Using Outer Totality Cellular Automata (OTCA)

Design and Analysis of Imaging Chip using High-Speed AXI-Interface for MPSOC Applications on FPGA Platform

Surface Characteristics Measurement Using Computer Vision: A Review

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