QuSyn Technologies

Internship Opportunity: Image Processing & Automation We are seeking a motivated intern to join our team in developing robust, rule-based image processing algorithms for automated data acquisition. ** Image processing expertise is a must. Position Details Duration : 23 months initially. Extendable depending on progress. Mode : On-site Stipend : 20,00025,000 INR per month (based on experience, performance and mode of engagement). Engagement : Regular check-ins, progress reviews, and collaborative feedback loops Scope of Work Image Denoising & Background Removal : Design and implement classical algorithms to clean noisy images and remove backgrounds across varied conditions. Foreground Extraction : Accurately isolate foreground elements using rule-based segmentation, contour analysis, and pixel-level heuristics. Pixel-to-Data Conversion : Translate foreground pixel information into structured data formats (arrays) for downstream use. Full Automation for Zero Human Intervention : Build a framework that autonomously processes raw images into usable data without manual oversight. Benchmarking the algorithm against a lower bound of image quality : Defining and validating the minimum resolution, contrast, and noise levels under which the framework still performs reliably using quantitative metrics and thresholds and stress testing with degraded inputs. Required Skills Strong foundation in classical image processing (thresholding, morphological ops, edge detection, etc.) Proficiency in Python and libraries like OpenCV, NumPy, PIL Algorithmic thinking and modular design Pixel-level analysis and data structuring Automation mindset with robust scripting practices Familiarity with image quality metrics (PSNR, SSIM, entropy) Clear documentation and reproducibility How to Apply: Interested candidates should attach a single PDF with: Resume or CV highlighting relevant image processing experience. A short write-up proposing a possible solution to the problem using classical image processing techniques (assume medical images) explaining feasibility of their approach, especially in the context of noisy (or low-quality) images and automation. Please use the subject line: Application Image Processing Internship . Shortlisted candidates will be invited to give a brief presentation on their proposed solution, including rationale, expected performance, and benchmarking strategy.