Holographic Element Detection in Video Streams
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Solution Overview
Problem
Existing methods for image search and recognition, such as those described in Russian Patent No. RU 2266565, face challenges in robustness due to glare, leading to potential inaccuracies in detecting and localizing holograms in video streams.
Innovation Solution
A method and system for detecting and localizing holograms in a video stream that stabilizes document images, constructs saturation and color tone maps, analyzes color characteristics, calculates changes between frames, and combines estimates to create an integrated map for determining holographic element regions, thereby enhancing robustness against noise and glare.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional image search and recognition methods are used, then the detection process is simple, but the robustness deteriorates in the presence of glare
Solution Approach 1:
The patent segments the detection process into multiple independent modules: color space conversion module, saturation map construction module, color tone map construction module, histogram analysis module, change estimation module, and integrated map construction module. Each module processes specific aspects of hologram detection, allowing the system to maintain robustness against glare while keeping each individual module relatively simple and manageable.
Solution Approach 2:
The patent transforms the detection problem from standard RGB color space to HSV color space, adding dimensional separation between color information (hue) and intensity information (value). This dimensional change allows the detection algorithm to focus on hue and saturation characteristics that are invariant to glare-induced brightness changes, thereby improving robustness without significantly increasing computational complexity.
2Measurement precision
If multiple processing steps are applied to improve accuracy, then detection accuracy is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary color space conversion to HSV and pre-computes saturation and color tone maps before conducting the actual hologram detection. These preliminary processing steps organize the data in a way that facilitates faster subsequent analysis, allowing multiple processing steps to be applied without proportionally increasing total processing time.
Solution Approach 2:
The patent employs periodic action by computing histograms over fixed intervals and comparing current frame histograms with previous frame histograms at regular intervals. This periodic comparison approach enables efficient change detection over time, maintaining high detection accuracy while controlling processing time through structured, interval-based analysis rather than continuous processing.
3Measurement precision
If histogram comparison between frames is performed, then change detection accuracy is improved, but computational load increases
Solution Approach 1:
The patent extracts only the essential histogram characteristics (color tone distribution) from each frame for comparison, rather than processing all pixel data. By taking out and focusing on the relevant color tone histogram features that indicate hologram presence, the system achieves accurate change detection while significantly reducing computational load compared to full-image processing.
Solution Approach 2:
The patent changes the parameter space for comparison from raw pixel values to histogram-based color tone distributions. This parameter transformation reduces the dimensionality and complexity of the comparison operation, enabling accurate detection of color characteristic changes between frames while maintaining lower computational load through efficient histogram operations.
Data Source
AI summary
A method for detecting holographic elements in a video stream containing images in the form of documents includes: processing of a video stream in which the document image is stabilized; constructing saturation and color tone maps; analyzing color characteristics in image regions; constructing histograms of color characteristics; estimating a change in the color characteristics at least in part based on data obtained by calculating a difference between the histograms of a current and a previous frame; constructing an integrated map of hologram presence estimates by combining calculated estimates for all video stream frames based at least in part on the estimation of the change in color characteristics; and determining final regions of the holographic elements based at least in part on the integrated map of the hologram presence estimates.