Vector Data Processing for Image Throughput
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image processing technologies are inefficient in processing large amounts of image data, often requiring extensive time and resources, which hinders real-time processing capabilities.
Innovation Solution
The proposed solution involves an image processing apparatus and method that utilizes a vector data manager to convert image data into vector data, which is then processed by a vector processor, with a synchronizer controlling the timing of data transmission and processing to enhance efficiency and speed. This apparatus includes line and kernel memories for storing pixel data and a vector data control unit for converting pixel kernel data into vector data, allowing for efficient two-dimensional vector processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional image processing methods are used to process large amounts of image data, then processing completeness is achieved, but processing time increases significantly and real-time processing capability deteriorates
Solution Approach 1:
The patent divides the image data processing into multiple segments by extracting pixel kernels from different regions of the image data and processing them in parallel through multiple vector processors. This segmentation enables simultaneous processing of multiple image regions, significantly improving throughput and reducing overall processing time while maintaining complete processing of all image data
Solution Approach 2:
The patent transforms two-dimensional pixel kernel data into one-dimensional vector data for processing. This dimensional transformation allows the vector processors to handle image data more efficiently by converting spatial relationships into linear sequences that can be processed faster, thereby improving processing speed without sacrificing processing completeness
2Productivity
If more memory access operations are performed to handle large image data, then data processing completeness is maintained, but processing efficiency decreases
Solution Approach 1:
The patent performs preliminary extraction of pixel kernels from image data before main processing operations. By pre-identifying and extracting the necessary pixel kernel regions that contain relevant processing information, the system reduces the volume of data requiring subsequent memory access and processing, thereby improving efficiency while maintaining complete processing of all necessary image information
Solution Approach 2:
The patent extracts pixel kernels from larger image data structures, isolating only the essential processing units needed for vector operations. This extraction removes unnecessary data from the processing pipeline, reducing memory access requirements and operational complexity while ensuring all critical image data is processed
Data Source
AI summary
Disclosed are an image processing apparatus and method that more efficiently process image data. The image processing apparatus includes a vector data manager that receives at least some of all image data and converts the received image data into vector data, a vector processor that receives the vector data from the vector data manager, performs a vector processing operation by using the vector data, and generates output vector data as a result of the vector processing operation, and a synchronizer that controls a timing of when the vector data manager transmits the vector data to the vector processor.