Auto-detect 3D Image Format via Luminance Analysis
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Solution Overview
Problem
3D display devices face unsatisfactory playback quality when they fail to switch to the correct playback mode for 3D images/videos, as they are often played in 2D mode, leading to issues like the SBS 3D video being divided into left and right halves.
Innovation Solution
An auto-detect method that divides single-frame images into macro-blocks and sub-blocks, calculates pixel luminance sum characteristic values, and determines the similarity between image halves to accurately identify 2D, 3D SBS, or 3D TB formats, thereby switching to the appropriate playback mode.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the 3D display device uses manual mode selection for image formats, then the device complexity is reduced, but the ease of operation deteriorates as users cannot automatically detect and switch to correct playback modes
Solution Approach 1:
The image is divided into multiple macro-blocks, which are further divided into sub-blocks, and then into meta-blocks for analysis. This segmentation allows the system to compare specific regions (left vs right halves, upper vs lower halves) to detect SBS and TB formats without analyzing the entire image at once, reducing computational complexity while maintaining detection accuracy
Solution Approach 2:
The patent replaces manual mechanical mode selection with an automated digital detection system that uses pixel luminance sum calculations and confidence thresholds to automatically identify image formats and switch playback modes, eliminating the need for user intervention
2Reliability
If the display device plays 3D images in 2D mode, then the playback quality deteriorates, but the device complexity remains low as no format detection is performed
Solution Approach 1:
The system calculates confidence values based on pixel luminance sum comparisons and uses these feedback results to automatically determine the correct playback mode. The confidence thresholds provide a feedback mechanism that ensures reliable format detection and appropriate mode switching, improving playback quality without requiring complex manual intervention
Solution Approach 2:
The display device performs self-detection of image formats using automated algorithms that analyze pixel luminance characteristics. The system serves itself by automatically detecting SBS, TB, or 2D formats and switching to the appropriate playback mode without external intervention, ensuring reliable playback quality
3Measurement precision
If the system divides images into multiple blocks for analysis, then the measurement precision of format detection improves, but the processing time increases
Solution Approach 1:
The image is segmented into macro-blocks, sub-blocks, and meta-blocks to enable precise local comparisons between left/right and upper/lower halves. This segmentation improves measurement precision by allowing targeted analysis of specific regions while maintaining manageable processing complexity through hierarchical division
Solution Approach 2:
The system performs partial action by analyzing only the necessary regions (comparing left vs right halves for SBS, upper vs lower halves for TB) rather than processing every pixel uniformly. This selective analysis improves detection accuracy for specific formats while reducing overall processing time compared to exhaustive analysis
Data Source
AI summary
An auto-detect method for detecting a single-frame image format is provided. A single-frame image is divided into a plurality of macro-blocks. Each of the macro-blocks is divided into a plurality of sub-blocks. A meta-block is allocated in each of the sub-blocks. A pixel luminance sum characteristic value for each of the meta-blocks is calculated. A first confidence between a left half and a right half of the single-frame image is calculated according to the pixel luminance sum characteristic values. A second confidence between an upper half and a lower hap of the single-frame image is calculated according to the pixel luminance sum characteristic values. A format of the single-frame image is determined according to the pixel luminance sum characteristic values, and the first and second confidences of the single-frame image.