OpenCV Expert for Test Strip Image Quality & Environmental Analysis Module Development
Budget: $250 – $750 USD
We are seeking an experienced OpenCV expert to develop an image quality and environmental analysis module for urinalysis test strips. The module will assess and ensure the quality of images submitted by users, focusing on factors like lighting, sharpness, exposure, and alignment of the test strip in the image.
The goal is to provide users with real-time feedback when image quality is insufficient (e.g., “Adjust lighting” or “Retake due to blur”), ensuring only high-quality images are used for accurate health diagnostics. Responsibilities:
Develop a test strip image quality detection module using OpenCV.
Analyze environmental factors such as lighting, focus, sharpness, and alignment to determine image quality.
Provide real-time feedback to users for improving image quality (e.g., retake instructions).
Implement preprocessing techniques for automated adjustments to contrast, brightness, and sharpness to enhance image clarity.
Collaborate with other developers for seamless module integration.
Conduct testing to ensure the module works effectively on various devices and environments.
(Optional) Use machine learning techniques to improve image recognition accuracy.
Requirements:
Proven expertise in OpenCV with 3+ years of experience.
Proficiency in Python or C++ for image processing.
Strong knowledge of image quality metrics such as sharpness, brightness, and focus.
Familiarity with blur detection, edge detection, and image preprocessing methods.
Self-motivated with the ability to work independently and meet deadlines.
(Optional) Experience with machine learning for image classification is a plus.
The goal is to provide users with real-time feedback when image quality is insufficient (e.g., “Adjust lighting” or “Retake due to blur”), ensuring only high-quality images are used for accurate health diagnostics. Responsibilities:
Develop a test strip image quality detection module using OpenCV.
Analyze environmental factors such as lighting, focus, sharpness, and alignment to determine image quality.
Provide real-time feedback to users for improving image quality (e.g., retake instructions).
Implement preprocessing techniques for automated adjustments to contrast, brightness, and sharpness to enhance image clarity.
Collaborate with other developers for seamless module integration.
Conduct testing to ensure the module works effectively on various devices and environments.
(Optional) Use machine learning techniques to improve image recognition accuracy.
Requirements:
Proven expertise in OpenCV with 3+ years of experience.
Proficiency in Python or C++ for image processing.
Strong knowledge of image quality metrics such as sharpness, brightness, and focus.
Familiarity with blur detection, edge detection, and image preprocessing methods.
Self-motivated with the ability to work independently and meet deadlines.
(Optional) Experience with machine learning for image classification is a plus.