Image Processing Jobs

I'm seeking a proficient researcher and MATLAB expert who can assist in developing a research proposal aimed at enhancing Image Super-Resolution (SR) models. The proposed research should aim to tackle existing limitations such as high computational complexity, restricted upscaling factors, and inadequate restoration quality. Key Responsibilities: Research Proposal Development: Formulate a comprehensive proposal targeting the improvement of SR models. MATLAB Implementation: Implement the proposed model in MATLAB, ensuring it can be validated against current leading SR models. Model Validation: The model should be tested on BSD200, BSD100, and URBAN100 datasets. Algorithm Development: Create a low-complexity SR algorithm that offers improved computational efficiency. Performance ...

I have a set of medium-resolution images of a garment that contains several areas needing repair. This includes both torn and discolored spots. I need a specialist to manually inspect these images and identify the problematic areas. The ideal candidate for this task will have a keen eye for detail, experience in garment inspection and image analysis, and the ability to provide a comprehensive report on the condition of the garment.

I'm looking for a skilled professional who can assist in extracting both elliptical and rectangular text from a circle banner. The background of the banner will be varied, not a solid color or design, which adds complexity to the task. Key Tasks: - Determine the best grayscale conversion method for text extraction and convert the image to grayscale accordingly. - Determine the proper orientation of the image based on text phrases (as opposed to graphic elements or color patterns). - Rotate and save the image for optimal text extraction - Extract and save all text in plain text format, along with its corresponding quadrant from the image. - Identify and locate the position of a separate image within the main image using threshold matching. Ideal Skills and Experience: - Proficiency ...

1. Copy-Move Forgery Detection Challenges:  Post-processing transformations (e.g., rotation, scaling, flipping).  Limited generalization to diverse datasets.  Neglect of cross-image forgeries. Proposed Solutions: 1. Feature Extraction Enhancement: o Use deep learning models (e.g., CNNs with attention mechanisms) to detect transformation-invariant features. o Integrate transformer models for better spatial and contextual understanding. 2. Cross-Domain Learning: o Employ unsupervised domain adaptation techniques to enhance generalization across datasets. o Augment training datasets with synthetic forgery samples using Generative Adversarial Networks (GANs). 3. Multi-Modal Approaches: o Combine image metadata (EXIF) with visual features to improve detection in cross-image scenarios. o Leve...