Adaptive Camera Control for Reducing Motion Blur
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Solution Overview
Problem
Smartphones struggle to capture high-quality images of large objects due to the need to maintain distance, resulting in low resolution and blurred details, especially when imaging documents or scenes that require analysis, such as text recognition.
Innovation Solution
A method that combines multiple image frames to create a composite image, using positional data from inertial sensors and image features to align and improve image quality, allowing for high-resolution imaging of large objects by capturing segments from different angles and orientations, and applying real-time processing to adjust capture conditions and provide feedback to the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the smartphone camera is held at a distance from the object to capture the entire object, then the object can be fully imaged, but the image resolution and detail quality deteriorate
Solution Approach 1:
The patent divides the imaging task into multiple segments by capturing a sequence of images at different positions and orientations. Instead of attempting to capture the entire large object in a single frame from a distance, the system captures multiple close-up segments that are later stitched together to form a complete high-resolution composite image
Solution Approach 2:
The patent transitions from two-dimensional imaging (single frame) to three-dimensional imaging by capturing images from multiple positions and orientations in space. The inertial sensors track the camera's movement through 3D space, enabling the system to accumulate image data from different spatial dimensions and reconstruct a comprehensive high-resolution view
2Area of stationary object
If the camera captures images while moving to cover large areas, then the coverage area increases, but motion blur increases and image quality deteriorates
Solution Approach 1:
The system performs preliminary actions by capturing images at carefully controlled intervals during movement. The inertial sensors predict optimal capture moments and positions in advance, allowing the camera to capture sharp images at predetermined spatial intervals rather than continuously during motion
Solution Approach 2:
The inertial sensors provide real-time feedback about camera movement and position. This feedback is used to determine when to capture images and how to align them during stitching, ensuring that images are captured at optimal moments when motion blur is minimized while still covering the required area
3Manufacturing precision
If multiple image frames are captured and combined to improve resolution, then the image quality improves, but the processing time and complexity increase
Solution Approach 1:
The patent replaces complex manual alignment and stitching processes with automated computational methods. The inertial sensors provide precise positional data that automatically guides the alignment of multiple images, substituting mechanical alignment efforts with sensor-based digital registration
Solution Approach 2:
The system changes spatial parameters (position, orientation) systematically across multiple captures. By controlling and recording these parameter changes through inertial sensors, the system can mathematically reverse-engineer the correct alignment during stitching, transforming a complex alignment problem into a parameter-based registration task
Data Source
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AI summary
A method of forming a visual representation of an object from a plurality of image frames acquired using a portable electronic device, the method comprising the steps of determining at least one parameter of motion of the portable electronic device; determining an indication of blur; and conditionally selecting to discard one or more image frames based on the indication of blur.