Automatic 3D Object Watermarking Using Surface Roughness and Flow Degree
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Solution Overview
Problem
The existing methods for watermarking 3D objects are manual and costly, requiring laborious decision-making for placing watermarks, and are not scalable for large numbers of 3D works.
Innovation Solution
An apparatus and method for automatic visible watermarking of 3D data, which involves obtaining watermark parameters, determining target vertices on a 3D object, generating candidate boxes based on these vertices and watermark parameters, selecting target boxes that meet specific conditions such as low roughness and high flow degree, and embedding the watermark into these target boxes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual watermark embedding is used, then watermark placement quality can be controlled, but the process becomes laborious and costly
Solution Approach 1:
The system performs automatic watermark embedding by selecting candidate boxes and determining target boxes based on predefined criteria (roughness threshold, flow degree threshold) without requiring manual intervention. The apparatus autonomously completes the entire watermarking process from candidate generation to final embedding, eliminating laborious manual decision-making while maintaining quality through algorithmic selection.
Solution Approach 2:
The system uses quantitative parameters (roughness threshold, flow degree threshold, distance threshold) to objectively evaluate and select target boxes for watermark embedding. By transforming subjective quality assessment into measurable parameter comparisons, the system achieves consistent high-quality results automatically, resolving the contradiction between quality control and processing efficiency.
2Manufacturing precision
If manual watermark embedding is used, then watermark quality can be ensured, but the cost increases for large numbers of 3D works
Solution Approach 1:
The apparatus automatically selects candidate boxes and determines target boxes using predefined criteria (roughness threshold, flow degree threshold) without manual intervention. This self-service mechanism eliminates the need for expensive manual labor while maintaining consistent watermark quality through algorithmic evaluation of surface properties and box suitability.
Solution Approach 2:
The system replaces manual mechanical evaluation and placement with an automated computational system that uses mathematical criteria (roughness, flow degree, distance thresholds) to evaluate candidate boxes and determine optimal target locations. This substitution of manual processes with automated algorithms significantly reduces cost while maintaining quality.
3Productivity
If automatic watermark embedding is implemented, then efficiency increases, but ensuring watermark quality becomes challenging
Solution Approach 1:
The system ensures watermark quality through automated evaluation using quantitative parameters: roughness threshold to assess surface smoothness, flow degree threshold to evaluate box suitability, and distance threshold to maintain proper spacing. These measurable criteria enable consistent quality control without manual intervention, resolving the contradiction between automated efficiency and quality assurance.
Solution Approach 2:
The apparatus uses feedback from parameter evaluation (roughness, flow degree, distance measurements) to automatically determine whether candidate boxes meet the criteria for target box selection. This feedback mechanism ensures that only boxes satisfying quality thresholds are selected for watermark embedding, maintaining high quality while operating automatically.
4Manufacturing precision
If manual decision-making is used for watermark placement, then quality control is possible, but scalability is limited
Solution Approach 1:
The system autonomously selects candidate boxes and determines target boxes using predefined quality criteria (roughness threshold, flow degree threshold, distance threshold) without requiring manual decision-making. This self-service capability enables the system to handle any number of 3D works consistently, achieving both high placement accuracy and unlimited scalability.
Solution Approach 2:
The apparatus applies the same automated selection criteria and evaluation process to all 3D works regardless of quantity or complexity. The universal application of roughness, flow degree, and distance threshold evaluation enables consistent quality control across diverse datasets, making the system highly scalable while maintaining placement accuracy.
Data Source
AI summary
This disclosure relates to the field of data processing, and discloses an apparatus, method and readable storage medium for watermarking of 3D objects. In this method, the apparatus obtains 3D works (e.g. a 3D model) and watermark parameters of target watermarks to be embedded. And then, the apparatus can determine at least one target box on the 3D model meeting watermark filtering conditions based on the watermark parameters of the target watermarks. The conditions include at least one of roughness, flow degree, overlapping situation and distance of target boxes. After that, the apparatus can embed the target watermarks to the at least one target box on the 3D model. By doing so, the target watermarks can be embedded automatically, and the quality of the target watermarks can be improved due to the introduction of filtering conditions.