Deepesh Srivastava

Vini Katyal, Aviral, Deepesh Srivastava

Many images nowadays are captured from behind the glasses and may have certain stains discrepancy because of glass and must be processed to make differentiation between the glass and objects behind it. This research paper proposes an algorithm to remove the damaged or corrupted part of the image and make it consistent with other part of the image and to segment objects behind the glass. The damaged part is removed using total variation inpainting method and segmentation is done using kmeans clustering, anisotropic diffusion and watershed transformation. The final output is obtained by interpolation. This algorithm can be useful to applications in which some part of the images are corrupted due to data transmission or needs to segment objects from an image for further processing.

Vini Katyal, Deepesh Srivastava

This paper focuses on fruit defect detection and glare removal using morphological operations, Glare removal can be considered as an important preprocessing step as uneven lighting may introduce it in images, which hamper the results produced through segmentation by Gabor filters .The problem of glare in images is very pronounced sometimes due to the unusual reflectance from the camera sensor or stray light entering, this method counteracts this problem and makes the defect detection much more pronounced. Anisotropic diffusion is used for further smoothening of the images and removing the high energy regions in an image for better defect detection and makes the defects more retrievable. Our algorithm is robust and scalable the employability of a particular mask for glare removal has been checked and proved useful for counteracting.this problem, anisotropic diffusion further enhances the defects with its use further Optimal Gabor filter at various orientations is used for defect detection.