Suvadip Mukherjee

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We propose a novel region based segmentation method capable of segmenting objects in presence of significant intensity variation. Current solutions use some form of local processing to tackle intra-region inhomogeneity, which makes such methods susceptible to local minima. In this letter, we present a framework which generalizes the traditional Chan-Vese(More)
The development of social behavior is poorly understood. Many animals adjust their behavior to environmental conditions based on a social context. Despite having relatively simple visual systems, Drosophila larvae are capable of identifying and are attracted to the movements of other larvae. Here, we show that Drosophila larval visual recognition is encoded(More)
A segmentation framework is proposed to trace neurons from confocal microscopy images. With an increasing demand for high throughput neuronal image analysis, we propose an automated scheme to perform segmentation in a variational framework. Our segmentation technique, called tubularity flow field (TuFF) performs directional regional growing guided by the(More)
A segmentation framework is proposed to trace neurons from confocal microscopy images. With an increasing demand for high throughput neuronal image analysis, we propose an automated scheme to perform segmentation in a variational framework. Our segmentation technique, called tubularity flow field (TuFF) performs directional regional growing guided by the(More)
In this paper we propose a novel approach to the extraction of medial axis for grayscale objects. The method utilizes a computationally efficient vector field convolution to enhance the medialness feature. Local maxima of medialness are analyzed in scale space, yielding a robust medial axis for grayscale imagery. An important application of this work is the(More)
We propose a novel region based segmentation technique using dictionary learning. In a previous work we have developed a method which uses a set of pre-specified Legendre basis functions to perform region based segmentation of an object in presence of heterogeneous illumination. We hypothesize that in problems where a set of training images for the object(More)
The neuronal content of an organism, the individual morphology of each neuron and the variability of these components constitute the atlas of the neurome. The description of such an atlas will be critical in determining the complex neural system of a given organism, eventually providing clues to how animals think and function. As the organisms under(More)