mlsanityData to 7 Oct 2026

Research on Splicing Image Detection Algorithms Based on Natural Image Statistical Characteristics

arXiv 2404.16296 ↗First posted 25 Apr 2024cs.CV cs.AIcited by 20

Not on the map. Why?

Abstract (arXiv)

With the development and widespread application of digital image processing technology, image splicing has become a common method of image manipulation, raising numerous security and legal issues. This paper introduces a new splicing image detection algorithm based on the statistical characteristics of natural images, aimed at improving the accuracy and efficiency of splicing image detection. By analyzing the limitations of traditional methods, we have developed a detection framework that integrates advanced statistical analysis techniques and machine learning methods. The algorithm has been validated using multiple public datasets, showing high accuracy in detecting spliced edges and locating tampered areas, as well as good robustness. Additionally, we explore the potential applications and challenges faced by the algorithm in real-world scenarios. This research not only provides an effective technological means for the field of image tampering detection but also offers new ideas and methods for future related research.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). Builds on 2 of its 9 references that are in the map. First posted on arXiv 25 Apr 2024.

Builds on

2 of 9 references.

References · 2

  1. 2023VMT-Adapter: Parameter-Efficient Transfer Learning for Multi-Task Dense Scene Understandingcited by 62
  2. 2024Research on Detection of Floating Objects in River and Lake Based on AI Intelligent Image Recognitioncited by 6

Built on by

Cited by year

Citing papers per year: 2024: 7; 2025: 13.

20 papers.

Sort:

By area:

  1. 2024Real-Time Pill Identification for the Visually Impaired Using Deep Learningcited by 20
  2. 2024Enhance Image-to-Image Generation with LLaVA-generated Promptscited by 20
  3. 2024Enhanced Recommendation Combining Collaborative Filtering and Large Language Modelscited by 10
  4. 2025User Behavior Analysis in Privacy Protection with Large Language Models: A Study on Privacy Preferences with Limited Datacited by 8
  5. 2024Exploiting Diffusion Prior for Out-of-Distribution Detectioncited by 7
  6. 2025LLM-Driven E-Commerce Marketing Content Optimization: Balancing Creativity and Conversioncited by 7
  7. 2025Research on Personalized Financial Product Recommendation by Integrating Large Language Models and Graph Neural Networkscited by 6
  8. 2025Research on Model Parallelism and Data Parallelism Optimization Methods in Large Language Model-Based Recommendation Systemscited by 6
  9. 2025Meta-Learning for Cold-Start Personalization in Prompt-Tuned LLMscited by 5
  10. 2025RLHF Fine-Tuning of LLMs for Alignment with Implicit User Feedback in Conversational Recommenderscited by 5
  11. 2025Deep Learning Model Acceleration and Optimization Strategies for Real-Time Recommendation Systemscited by 3
  12. 2025LLM-Augmented Symptom Analysis for Cardiovascular Disease Risk Prediction: A Clinical NLPcited by 2
8 more
  1. 2025Propose and Rectify: A Forensics-Driven MLLM Framework for Image Manipulation Localizationcited by 2
  2. 2025Efficient Cold-Start Recommendation via BPE Token-Level Embedding Initialization with LLMcited by 2
  3. 2025Instructional Prompt Optimization for Few-Shot LLM-Based Recommendations on Cold-Start Userscited by 1
  4. 2024Research on Edge Detection of LiDAR Images Based on Artificial Intelligence Technologycited by 0
  5. 2024StableSemantics: A Synthetic Language-Vision Dataset of Semantic Representations in Naturalistic Imagescited by 0
  6. 2024Detecting Facial Image Manipulations with Multi-Layer CNN Modelscited by 0
  7. 2025Generating Multimodal Images with GAN: Integrating Text, Image, and Stylecited by 0
  8. 2025Multimodal Foundation Model-Driven User Interest Modeling and Behavior Analysis on Short Video Platformscited by 0