Automated Inspection Level Assignment for Printed Material Content
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing inspection systems struggle to intuitively match inspection levels with content attributes in printed materials, leading to inefficient defect detection and requiring manual user intervention to adjust inspection levels.
Innovation Solution
The proposed system generates a raster image from a print job, identifies content attributes distinct from object attributes, assigns inspection level information based on these attributes, and outputs the raster image with inspection level information for use as a reference in inspections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If inspection levels are set based on object attributes (text, graphics, image), then automated inspection level assignment is achieved, but the classification does not match user-intuitive content categories (person, character string, barcode)
Solution Approach 1:
The patent segments the classification process into two distinct stages: first, object attribute classification (text, graphics, image) is performed automatically by the RIP apparatus, and then content attribute classification (person, character string, barcode) is performed by the inspection apparatus. This segmentation allows each system to specialize in its strengths while maintaining overall automation.
Solution Approach 2:
The patent introduces an intermediary mechanism - the raster image data with embedded object attribute information - that bridges the RIP apparatus and inspection apparatus. The RIP apparatus adds object attribute information to the raster image, which then serves as a mediator carrying both visual and classification data to the inspection apparatus for further content-based classification.
2Device complexity
If a single classification system (object attribute) is used, then automated processing is simplified, but it cannot handle different inspection level requirements for different content types (person vs. other image content)
Solution Approach 1:
The patent applies local quality by assigning different inspection levels to different content attributes within the same printed material. The inspection apparatus can set higher inspection levels for critical content types like barcodes and persons, while using lower levels for other image content, allowing localized optimization of inspection strictness based on content importance.
Solution Approach 2:
The patent introduces dynamic inspection level adjustment based on content attributes. Instead of a fixed inspection level for all content, the system dynamically determines appropriate inspection levels by analyzing the raster image and identifying content attributes, then applying different inspection criteria accordingly.
3Measurement precision
If manual designation of areas and inspection levels is required for each content type, then precise inspection control is achieved, but user workload and time consumption increase significantly
Solution Approach 1:
The patent enables the inspection apparatus to perform self-service by automatically analyzing the raster image, identifying content attributes (person, character string, barcode, etc.), and determining appropriate inspection levels without requiring manual user intervention. The system serves itself by autonomously completing the entire inspection configuration process.
Solution Approach 2:
The patent performs preliminary classification and inspection level determination automatically before the actual inspection process begins. The inspection apparatus analyzes the raster image in advance, identifies all content attributes, and pre-assigns inspection levels, so that when inspection actually occurs, the system is already optimized and ready to execute without delays.
Data Source
AI summary
To make it possible to easily set an inspection level in accordance with the type of contents included in a printed material. First, based on PDL included in a print job, a raster image is generated and a contents attribute different from an object attribute predefined by the PDL is identified by analyzing the raster image. Then, inspection level information in accordance with the identified contents attribute is assigned to the generated raster image and the raster image is provided to an inspection apparatus.