Dynamic Perspective Transformation Engine Block Sizing
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Solution Overview
Problem
Current image processing techniques for vehicles with multiple external cameras are inefficient in utilizing hardware resources due to sub-optimal selection of block sizes for perspective transformation, particularly when dealing with distorted images from wide-angle or fisheye lenses, leading to resource underutilization and increased computing power requirements.
Innovation Solution
A dynamic configuration technique for a perspective transformation engine that determines regions and block sizes based on scale ratios, generating a scale ratio image, binary scale ratio image, and boundary ranges to optimize block sizes for each region, allowing for efficient processing of distorted images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If uniform block sizes are used for perspective transformation across the entire image, then the processing is simpler to implement, but hardware resource utilization is sub-optimal and computing power requirements increase
Solution Approach 1:
The image is divided into multiple regions based on scale ratio analysis, with each region assigned an appropriate block size. This segmentation allows the system to process different parts of the image with optimized parameters rather than applying a uniform approach, thereby improving hardware resource utilization while maintaining implementation feasibility through automated region detection and classification
Solution Approach 2:
The block size is made dynamic and adaptive to different regions of the image based on scale ratio characteristics. Rather than using a fixed uniform block size, the system dynamically determines optimal block sizes for each region, allowing the processing parameters to adapt to the local image characteristics and thereby improve overall processing efficiency
2Productivity
If larger block sizes are used for perspective transformation, then fewer blocks need to be processed reducing overhead, but processing precision decreases particularly for distorted regions
Solution Approach 1:
Different block sizes are assigned to different regions of the image based on their scale ratio characteristics and distortion levels. Regions with higher distortion or更重要的 features use smaller blocks for higher precision, while less critical regions use larger blocks for higher throughput. This local optimization ensures that precision is maintained where needed while maximizing overall processing efficiency
3Manufacturing precision
If smaller block sizes are used for perspective transformation, then processing precision improves particularly for distorted regions, but more blocks need to be processed increasing computing overhead
Solution Approach 1:
The system applies smaller block sizes locally only to regions that require higher precision, such as areas with significant distortion or important features, while using larger block sizes in regions where high precision is less critical. This selective approach maintains necessary transformation precision while avoiding the computational overhead of using small blocks throughout the entire image
Data Source
AI summary
A technique for determining regions and block sizes for configuring a perspective transformation engine including determining a set of scale ratios for images captured by a camera, generating a scale ratio image based on the set of scale ratios, determining a set of boundary ranges for the scale ratio image, generating a binary scale ratio image using the set of scale ratios of the scale ratio image, determining a set of regions based on the set of boundary ranges for the binary scale ratio image, determining a block size for each region of the determined set of regions, and outputting the determined set of regions and the determined block sizes.