Batch Image Recognition for Rock Deformation Analysis

The patent applies segmentation by dividing the batch processing task into multiple parallel streams, each handling different image types with specialized segmentation methods. The system segments images based on their characteristics (rock, soil, interface) and processes them simultaneously through different algorithms, thereby improving overall processing efficiency while maintaining accuracy for each image type.

The patent implements preliminary action through pre-processing steps that classify and prepare images before segmentation. By预先 (in advance) categorizing images into different types and selecting appropriate segmentation methods for each category, the system avoids the need to process all images through a single time-consuming method, thus reducing total processing time while maintaining accuracy.

The patent applies local quality by assigning different segmentation methods to different image types based on their specific characteristics. For example, rock images use one segmentation approach while soil images use another, and interface images use a third. This localized approach ensures high recognition accuracy for each image type while avoiding the need to implement all possible segmentation methods for every image, thus controlling system complexity.

The patent utilizes parameter changes by dynamically selecting segmentation methods based on image parameters such as color distribution, texture characteristics, and structural features. The system changes the processing parameters (segmentation algorithm selection) according to the detected image characteristics, achieving high accuracy without requiring a fixed complex multi-method system for all images.

The patent implements self-service by creating an automated system that performs image segmentation and rock characteristic analysis without human intervention. The system automatically classifies images, selects appropriate segmentation methods, processes the images, and extracts rock characteristics, thereby eliminating the need for manual data processing and significantly reducing both human resources and time consumption while maintaining high accuracy.

The patent applies mechanics substitution by replacing the manual mechanical process of data processing with an automated computer vision system. The system uses algorithms and image processing techniques to automatically segment images and extract rock characteristics, substituting human manual work with automated computational processes, thus improving productivity and reducing human resource requirements.