Mobile Camera Motion Detection and Blurring Control
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Solution Overview
Problem
Conventional mobile communication terminals with camera modules struggle to capture diverse motions of an object effectively, often resulting in blurred images due to inconsistent capture intervals, which fail to accurately represent the object's motion.
Innovation Solution
A method and apparatus that determine if blurring has occurred in a frame by comparing it with a previous frame, and if not blurred, measure the motion by comparing the current frame with a pre-stored previous frame. If the motion is greater than a reference amount, the frame is stored as a photo file, ensuring only clear images with significant motion are captured.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If continuous photography is performed at specified intervals, then the quantity of photographs is increased, but the quality of photographs deteriorates due to blurring from inconsistent capture intervals
Solution Approach 1:
The patent applies feedback by analyzing the captured frame to detect blurring and motion characteristics, then using this analysis to determine whether to store the frame. The system continuously monitors frame quality metrics (blurring degree, motion amount) and adjusts storage decisions based on this feedback, ensuring that only high-quality frames with significant motion are saved, thereby resolving the contradiction between photograph quantity and quality
Solution Approach 2:
The patent changes the parameter of frame storage by introducing dynamic criteria based on blurring degree and motion amount. Instead of storing frames at fixed intervals regardless of quality, the system evaluates each frame's blurring parameter and motion parameter, storing only those that meet quality thresholds. This parameter-based selection resolves the contradiction by adapting storage decisions to actual frame quality rather than following a rigid timing schedule
2Quantity of substance
If all captured frames are stored, then the quantity of stored images is maximized, but the memory efficiency deteriorates due to storing blurred and redundant images
Solution Approach 1:
The patent extracts only the valuable frames from the continuous stream of captured images by applying quality filters. It identifies and extracts frames that are free from excessive blurring and exhibit significant motion, while discarding redundant blurred frames. This extraction process maximizes the number of useful stored images while minimizing memory waste, directly addressing the contradiction between image quantity and memory efficiency
Solution Approach 2:
The patent implements a discarding mechanism that selectively removes low-quality blurred frames from storage, while recovering and preserving high-quality frames with significant motion. By discarding redundant images that do not add value and recovering only the essential quality frames, the system optimizes memory usage while maintaining a substantial collection of useful photographs
3Measurement precision
If motion detection is added to improve photograph quality, then the precision of motion capture is improved, but the device complexity increases
Solution Approach 1:
The patent applies self-service by using the captured frame itself to detect motion and blurring, without requiring external sensors or complex additional hardware. The system extracts motion information and blurring characteristics directly from the image data, allowing the photographing system to self-evaluate and self-select frames based on their own content. This approach improves motion detection precision while minimizing added complexity
Data Source
AI summary
A method and an apparatus for taking pictures on a mobile communication terminal having a camera module are provided, which can control the photographing of an object in accordance with the motion of the object. The method includes generating a current frame by photographing an object, determining whether blurring has occurred in the current frame, measuring an amount of motion of the current frame if no blurring has occurred in the generated current frame, and storing the current frame if the measured amount of motion is greater than a pre-stored reference amount of motion.