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An open problem in biological image processing and analysis is the automated generation of neural atlases from image data. Such a neural atlas should be capable of representing typical neurons for each possible class. Further, the functioning atlas, called a neurome in this work, should enable the computation of neuron-to-neuron distances for the purposes of comparison and classification. Three technical...
Performance of an optical character recognition engine may be affected if the images are skewed and distorted due to perspective projection. In this paper, a computationally efficient skew correction technique has been presented for extracted text regions from business card images. The skew angle is estimated by analyzing the bottom and/or top profiles (height/depth from a horizontal base line) of...
Recent investigations in estimating object shape in images and leveraging knowledge of expected shapes to perform object segmentation have necessitated the formalization of a rigorous mathematical theory of shape. Most of the existing theory in nonlinear shape manifolds lacks physically meaningful parameterization of the shape components, for e.g., pose. We build a novel pose-shape manifold in which...
We have designed a novel query retrieval scheme for the information just in time (iJIT) system to retrieve handwritten annotations from digital documents based on typed/handwritten query. The two key components of the developed query retrieval system (QRS) are the character recognition engine and the query retrieval engine. The character recognition engine uses Tesseract 2.01 open source Optical Character...
We present a method for estimating cell population statistics on a high dimensional nonlinear cell manifold constructed from the output of a high throughput cytometer that allows microscopic imaging of each cell. After active contour segmentation of the cell images, we construct a nonlinear cell manifold from the morphology characteristics and multispectral properties of the cells. We estimate the...
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