Biomedical subjects
Publications and source records attributed to Subhasis Chaudhuri.
A novel image-based defect identification and coding technique has been proposed for fluted ingots, which are used for the production of locomotive wheels. The edge density map has been used for defect identification and an object-based coding approach has been applied for the storage of defective ingots. The complete scheme has been implemented in one of the integrated steel plants of India.
A system for retrieval of an unstructured environment under static and dynamic scenarios is proposed. The use of cylindrical mosaics or omnidirectional images is exploited for providing a rich description about the surrounding environment spanning 360 degrees. The environment description is based on defining the attributes of the nodes of a graph derived from the angular partitions of the captured images. Content-based image retrieval for each of these partitions is performed on an exemplar image database to annotate the nodes of the graph. The complete environment description is recovered by collating the retrieval results over all the partitions based on a simple voting scheme. This offers a qualitative description of the location in a totally natural and unstructured surrounding. The experiments yield quite promising results.
We propose a technique for super-resolution imaging of a scene from observations at different camera zooms. Given a sequence of images with different zoom factors of a static scene, we obtain a picture of the entire scene at a resolution corresponding to the most zoomed observation. The high-resolution image is modeled through appropriate parameterization, and the parameters are learned from the most zoomed observation. Assuming a homogeneity of the high-resolution field, the learned model is used as a prior while super-resolving the scene. We suggest the use of either a Markov random field (MRF) or an simultaneous autoregressive (SAR) model to parameterize the field based on the computation one can afford. We substantiate the suitability of the proposed method through a large number of experimentations on both simulated and real data.
We address the problem of simultaneous estimation of scene structure and restoration of images from blurred photometric measurements. In photometric stereo, the structure of an object is determined by using a particular reflectance model (the image irradiance equation) without considering the blurring effect. What we show is that, given arbitrarily blurred observations of a static scene captured with a stationary camera under different illuminant directions, we still can obtain the structure represented by the surface gradients and the albedo and also perform a blind image restoration. The surface gradients and the albedo are modeled as separate Markov random fields, and a suitable regularization scheme is used to estimate the different fields as well as the blur parameter. The results of the experimentations are illustrated with real as well as synthetic images.
A new concept called defocus morphing in real aperture images is introduced. View morphing is an existing example of shape-preserving image morphing based on the motion cue. It is proved that images can also be morphed based on the depth-related defocus cue. This illustrates that the morphing operation is not necessarily a geometric process alone; one can also perform a photometry-based morphing wherein the shape information is implicitly buried in the image intensity field. A theoretical understanding of the defocus morphing process is presented. It is shown mathematically that, given two observations of a three-dimensional scene for different camera parameter settings, we can obtain a virtual observation for any camera parameter setting through a simple nonlinear combination of these observations.
This paper describes a unique single camera-based dimension storage method for image-based measurement. The system has been designed and implemented in one of the integrated steel plants of India. The purpose of the system is to encode the frontal cross-sectional area of an ingot. The encoded data will be stored in a database to facilitate the future manufacturing diagnostic process. The compression efficiency and reconstruction error of the lossy encoding technique have been reported and found to be quite encouraging.
This paper describes a unique single camera-based dimensional measurement with a self-calibration method of image-based measurement. The system has been designed and implemented in one of the integrated steel plants in India. The purpose of the system is to obtain the frontal cross-sectional area of an ingot irrespective of its distance from the camera head. Automatic calibration is achieved by attaching a magnetic template of known area. This self-calibrating system is further refined to correct for the various distortions arising out of lens characteristics. The results obtained through field trials have been reported and found to be quite encouraging.