Image Processing Unit for Tethered Shooting Detail Confirmation
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Solution Overview
Problem
In commercial shooting scenarios, particularly during tethered shooting, confirming multiple images for various details such as facial expressions, product conditions, and lighting is inefficient due to the need for prolonged PC operations and varying points of interest among staff members, leading to complex and time-consuming image confirmation processes.
Innovation Solution
An image processing device that specifies a target pixel area containing a subject of interest within an image, using image analysis techniques like object recognition, personal identification, and posture estimation to automatically identify and enhance or synthesize this area across multiple images, allowing for efficient confirmation of specific details without manual operation in each image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple images are sequentially captured and displayed with manual enlargement operations, then detailed confirmation of each image is possible, but the confirmation time becomes extremely long
Solution Approach 1:
The system performs preliminary actions by automatically detecting and marking target pixel areas in advance before the user needs to examine details. The image processing unit identifies regions containing subjects of interest and prepares enlarged views ready for immediate display, eliminating the need for manual enlargement operations during the confirmation process.
Solution Approach 2:
The system creates copied and enlarged versions of specific pixel areas from the original images. The display control unit generates multiple copies of identified target regions at different magnification levels, allowing users to examine details without repeatedly processing the full-resolution original images, thus reducing confirmation time while maintaining detail accuracy.
2Measurement precision
If manual enlargement operations are performed on each image to check specific points, then detailed inspection is achieved, but the operation complexity increases
Solution Approach 1:
The system performs self-service by automatically identifying and preparing target pixel areas without requiring manual user operations. The image processing unit autonomously detects subjects of interest and generates appropriate enlarged views, allowing the system to serve the user's inspection needs without the user having to perform complex manual enlargement and navigation operations.
Solution Approach 2:
The system replaces manual mechanical operations (mouse clicks, drag operations for enlargement) with automated image processing algorithms. The computer automatically performs the functions that would otherwise require manual user interaction, substituting mechanical user actions with automated software-based image analysis and display control.
3Reliability
If different staff members check various points in images, then comprehensive quality confirmation is achieved, but the confirmation process becomes complicated
Solution Approach 1:
The system provides universal functionality that serves multiple staff members with different inspection needs through a single unified interface. The image processing unit can identify and display various types of subjects (faces, products, defects) in a consistent manner, allowing different users to focus on their specific areas of interest without needing different tools or complex coordination procedures.
Data Source
AI summary
An image processing device includes an image processing unit that specifies a target pixel area including a target subject from an image to be processed and performs image processing using the specified target pixel area.