Camera Sensor Alignment via Predominant Line Angle Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing camera-based systems for optical character recognition (OCR) on portable devices provide slow feedback for aligning the camera with text data, making it difficult for users, especially visually impaired individuals, to achieve proper alignment for efficient OCR quality.
Innovation Solution
A method that captures images, adapts contrast, performs binarization and edge filtering, and uses a robust algorithm like Hough transformation to detect the predominant alignment line angle, providing immediate user feedback through audio, tactile, or LED signals to assist in aligning the camera with text data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional feedback methods (visual display or acoustic instructions) are used for camera alignment, then the system provides alignment guidance, but the feedback is slow and difficult for visually impaired users to perceive and act upon
Solution Approach 1:
The patent implements immediate feedback by detecting the predominant alignment line angle of text in the captured image and providing real-time guidance to the user for adjusting camera orientation. The system continuously monitors image content and provides feedback signals (visual, acoustic, or tactile) that immediately reflect the current alignment status, enabling users to quickly adjust the camera position without waiting for delayed processing or interpretation of complex visual displays.
Solution Approach 2:
The patent replaces traditional mechanical alignment methods (manual trial-and-error positioning) with an automated optical detection system. The system uses image processing algorithms to automatically detect text line orientations and calculate the predominant alignment angle, substituting manual mechanical adjustment with automated optical measurement and computational analysis.
2Measurement precision
If complex image processing algorithms are used to detect text alignment, then detection accuracy improves, but processing time increases
Solution Approach 1:
The patent extracts only the essential feature needed for alignment detection - the predominant orientation angle of text lines - from the complex image data. Instead of analyzing all image characteristics, the system focuses specifically on detecting line orientations and angles, extracting only the relevant alignment information while ignoring other image features that would consume processing resources.
Solution Approach 2:
The patent transforms the image data into a different parameter space by detecting line angles and orientations rather than working directly with pixel intensities. This parameter transformation converts complex image processing into simpler geometric analysis of line orientations, changing the problem from intensity-based processing to angle-based measurement, which is computationally more efficient.
Data Source
Figure 1~2
AI summary
The present invention relates to a method for aligning a camera sensor to a significant data to be recognized comprising the steps of: a) capturing an image of the significant data by means of the camera sensor; b) contrast adaption, shade compensation and adaptive binarization of the image to obtain an artifact reduced image; c) edge and line filtering of the artifact reduced image to obtain an edge and line enhanced image; d) transformation of the edge and line enhanced image by means of a robust algorithm for predominant significant data line angle detection of the significant data contained in the image in respect to a horizontal line of the camera sensor, such as to obtain a predominant significant data line, the predominant significant data line angle representing the inclination of the predominant significant data line in respect to the horizontal line; and e) generating an user feedback signal dependent on the predominant significant data line angle.