Panorama Image Processing Gyroscope Feature Prediction
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Solution Overview
Problem
Panoramic photography is challenging for ordinary users to execute consistently due to difficulties in maintaining consistent camera rotation without tripods, affecting the quality of the final panoramic image.
Innovation Solution
An image processing method utilizing a gyroscope to predict features in a second image and matching them with features from a first image using Euclidean distance, discarding features exceeding a predetermined distance, and calculating a rotation matrix to correlate the images, thereby improving the consistency of rotation angles and accuracy in forming a panoramic image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually rotate the camera to capture multiple images for panoramic photography, then the panoramic image can be created, but the rotation consistency deteriorates making it difficult to control without tripods
Solution Approach 1:
The patent replaces manual mechanical camera rotation with an automated system using gyroscope sensors to detect rotation angles and a processor to control image capture timing. The gyroscope measures the actual rotation angle between images, eliminating the need for users to manually maintain rotation consistency.
Solution Approach 2:
The system implements feedback by using the gyroscope to continuously monitor the rotation angle during image capture and adjusting the capture timing based on the detected rotation. The processor receives real-time rotation data and uses it to determine when to capture the next image, ensuring consistent rotational intervals.
2Device complexity
If feature matching is performed without filtering predicted features, then processing is simpler, but matching accuracy deteriorates due to inclusion of incorrect features
Solution Approach 1:
The patent applies local quality by treating different features differently based on their reliability. Predicted features from gyroscope data are given higher weight and used to filter out inconsistent features. The system selectively accepts or rejects features based on their correspondence with predicted locations, improving overall matching accuracy.
Solution Approach 2:
The system performs preliminary action by predicting feature locations in the second image using gyroscope rotation data before actual feature extraction. This predicted feature set is used as a reference to filter and validate the features extracted from the second image, ensuring only consistent features are used for matching.
3Quantity of substance
If all extracted features are used for image correlation, then more information is utilized, but processing time increases and accuracy decreases due to inclusion of erroneous features
Solution Approach 1:
The patent discards features that do not match the predicted feature locations within a predetermined distance threshold. By comparing extracted features with gyroscope-predicted positions, the system eliminates inconsistent features while retaining valid ones, thus reducing the number of features to process while maintaining quality.
Solution Approach 2:
The system changes the parameter of feature selection by introducing a distance threshold parameter. Features are accepted or rejected based on whether their distance from predicted positions falls within this threshold, optimizing the balance between the number of features used and processing efficiency.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the accuracy and convenience of creating panoramic images by improving the consistency of rotation angles, allowing for effective image stitching even with handheld devices like mobile phones and digital cameras, reducing processing time and improving image quality.
Implementation Method 1
a gyro receives location information of the image processing device
Implementation Method 2
The first features and the second features are matched by Euclidean distance and removing the predicted features that exceed a predetermined distance from the second features
Implementation Method 3
The rotation matrix relationship between the first image and the second image are calculated by Euler angle
Data Source
AI summary
An image processing method for obtaining a panoramic image includes obtaining a first image and a second image by a camera unit, and obtaining location information between the viewpoints of the first image and the second image by a gyro. First features of the first image and second features of the second image are obtained according to a feature-capturing algorithm when pixel brightness differences exceed a threshold. Predicted features in the second imam are obtained by the location information, and predicted features that exceed a predetermined distance from the second features are discarded. A panorama image is obtained by combining the first image and the second image according to the first features and the selected second features.