Image Analysis Memory Reduction via Sequential Line Processing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image analyzing apparatuses require significant memory usage to determine whether a predetermined region near a subject group contains pixels not contiguous to the subject group, as they need to check multiple line pixel groups, leading to inefficient processing.
Innovation Solution
The apparatus sequentially identifies line pixel groups from one side to the other in a first direction, using relevant information from one side to determine the presence of non-contiguous pixels within a subject group without relying on line pixel groups from the other side, thereby reducing memory usage by only storing one binary line at a time in the working area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the noise remover checks multiple line pixel groups (seven line pixel groups) to determine whether a notable point is noise, then the determination accuracy is improved, but the memory usage amount increases
Solution Approach 1:
The patent divides the image data processing into separate processing units (one processing unit per line pixel group) that can operate independently. Each processing unit handles one line pixel group at a time, allowing the system to process multiple line pixel groups without loading them all into memory simultaneously. This segmentation enables accurate noise determination across multiple line pixel groups while maintaining low memory usage by processing data in discrete, manageable units.
Solution Approach 2:
The patent performs preliminary processing of line pixel groups before they are needed for noise determination. By pre-processing and preparing line pixel group data in advance (converting to binary data, identifying notable points, etc.), the system can retrieve only the necessary pre-processed data when needed, rather than loading and processing all seven line pixel groups simultaneously in memory. This preliminary action reduces the memory burden while maintaining determination accuracy.
2Reliability
If the apparatus stores multiple binary lines in the working area to check surrounding regions, then the processing completeness is improved, but the memory usage amount increases
Solution Approach 1:
The patent extracts only the essential data elements needed for noise determination from the line pixel groups. Instead of storing complete binary line data for multiple line pixel groups in memory, the system extracts and retains only the critical information (notable point positions, binary values at specific positions) required for accurate noise determination. This extraction approach ensures processing completeness by keeping necessary data while minimizing memory usage by eliminating redundant information.
3Measurement precision
If the noise remover processes each notable point by checking multiple line pixel groups, then the noise identification accuracy is improved, but the processing time increases
Solution Approach 1:
The patent performs preliminary identification of notable points and conversion of line pixel groups to binary data before the actual noise determination process. By preparing the data structure and identifying notable points in advance, the system reduces the computational burden during the noise determination phase. When checking surrounding line pixel groups for noise determination, the pre-processed binary data allows for faster retrieval and comparison, thereby reducing processing time while maintaining accurate noise identification.
Solution Approach 2:
The patent segments the noise determination process into independent operations for each notable point, using separate processing units that can potentially operate in parallel. By dividing the overall processing task into discrete segments (one per notable point), the system can optimize the checking of surrounding line pixel groups for each point independently, reducing the cumulative processing time while maintaining comprehensive noise identification accuracy.
Data Source
AI summary
In an image analyzing apparatus, a controller in a first analyzing process performs: sequentially identifying line pixel groups from a first side in a first direction; and determining whether a first-type pixel not contiguous to a first subject group constituted by at least one first-type pixel contiguous to each other in a second direction is present in a first region surrounding the first subject group, using first relevant information relating to each line pixel group located on the first side. In a second analyzing process, the controller performs: sequentially identifying the line pixel groups from a second side in the first direction; and determining whether the first-type pixel not contiguous to the first subject group is present in a second region surrounding the first subject group, using second relevant information relating to each line pixel group located on a second side.