Journal of Real-Time Image Processing

Aims & Scope

The Journal of Real-Time Image Processing is intended to bridge the gap between the theory and practice of image processing, serving the greater community of researchers, practicing engineers, and industrial professionals who deal with designing, implementing or utilizing image processing systems which must satisfy real-time design constraints.

The journal solicits original contributions in the following areas: • Real-time image and video processing algorithms • Real-time embedded image/video processing systems • Real-time image and video processing hardwa re and architecture including FPGA, DSP, GPU, GPP, ASIC, System-on-Chip (SoC), and System-in-a-Package (SiP) implementations • Real-time software optimizations and related design paradigms for image/video processing • Real-time hardware/software co-design for image and video processing • Real-time image and video processing applications including digital, cell-phone, and smart cameras, machine vision, industrial inspection, surveillance and security, image and video compression for transmission and for database storage and retrieval, biomedical imaging, spectral imaging, etc.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	3
2024	2.90

Journal Rank

Year	Value
2024	10045

Journal Citation Indicator

Year	Value
2024	1527

SJR (SCImago Journal Rank)

Year	Value
2024	0.578

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	47

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Slim-neck by GSConv: a lightweight-design for real-time detector architectures

  Citation: 328

  Authors: Hulin, Jun, Hanbing, Zheng, Zhenfei, Qiliang

• Fall detection system using Kinect’s infrared sensor

  Citation: 255

  Authors: Georgios, Dimitrios

• Real-time human action recognition based on depth motion maps

  Citation: 227

  Authors: Chen, Kui, Nasser

• A novel PCA–whale optimization-based deep neural network model for classification of tomato plant diseases using GPU

  Citation: 218

  Authors: Thippa Reddy, Dharmendra Singh, M. Praveen Kumar, Kuruva, Sweta, Saurabh, Alireza, Mamoun

• Review of stereo vision algorithms and their suitability for resource-limited systems

  Citation: 213

  Authors: Beau, Dah Jye, Kirt, James

• Real-time video fire/smoke detection based on CNN in antifire surveillance systems

  Citation: 178

  Authors: Sergio, Abdussalam, Alessio

• An innovative algorithm for key frame extraction in video summarization

  Citation: 149

  Authors: Ciocca, Schettini

• Deep learning model for real-time image compression in Internet of Underwater Things (IoUT)

  Citation: 146

  Authors: N., Mohamed, M., Mahmoud M., K.

• Efficient next-best-scan planning for autonomous 3D surface reconstruction of unknown objects

  Citation: 130

  Authors: Simon, Christian, Tim, Michael

• Coverless real-time image information hiding based on image block matching and dense convolutional network

  Citation: 123

  Authors: Yuanjing, Jiaohua, Xuyu, Yun, Qiang, Lingyun

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