Patent application number | Description | Published |
20100299379 | Non-Negative Matrix Factorization as a Feature Selection Tool for Maximum Margin Classifiers - Non-negative matrix factorization, NMF, is combined with identification of a maximum margin classifier by minimizing a cost function that contains a generative component and the discriminative component. The relative weighting between the generative component and the discriminative component are adjusting during subsequent iterations such that initially, when confidence is low, the generative model is favored. But as the iterations proceed, confidence increases and the weight of the discriminative component is steadily increased until it is of equal weight as the generative model. Preferably, the cost function to be minimized is: | 11-25-2010 |
20110191400 | L1 Projections with Box Constraints - Similarities between simplex projection with upper bounds and L | 08-04-2011 |
20110194690 | Data Adaptive Message Embedding For Visible Watermarking - A watermarking system uses distinct bit patterns to identify a logic 0, a logic 1, and a marker bit, which demarcates segments of logic bit information. Marker bits, which are printed on both foreground and background areas of an image, outline message blocks. In message extraction, a preprocessing step removes any white boarders, identifies the best defined corner of a message block, crops the image, and rotates the image to place the identified corner at the top-left corner. Message extraction scans the rotated image in window segments of increasing size during multiple cycles. During each cycle, if a bit pattern cannot be identified as a data bit, then the size of the examined bit area is increased and rechecked to see it specifically is a marker bit. If no bit information can be definitively identified, then it is assigned a logic bit value based on a 50% random assignment. | 08-11-2011 |
20110194725 | Novel Bit Pattern Design For Visible Watermarking - A watermarking system uses distinct bit patterns to identify a logic 0, a logic 1, and a marker bit, which demarcates segments of logic bit information. Marker bits, which are printed on both foreground and background areas of an image, outline message blocks. In message extraction, a preprocessing step removes any white boarders, identifies the best defined corner of a message block, crops the image, and rotates the image to place the identified corner at the top-left corner. Message extraction scans the rotated image in window segments of increasing size during multiple cycles. During each cycle, if a bit pattern cannot be identified as a data bit, then the size of the examined bit area is increased and rechecked to see it specifically is a marker bit. If no bit information can be definitively identified, then it is assigned a logic bit value based on a 50% random assignment. | 08-11-2011 |
20110194726 | Embedded Message Extraction For Visible Watermarking - A watermarking system uses distinct bit patterns to identify a logic 0, a logic 1, and a marker bit, which demarcates segments of logic bit information. Marker bits, which are printed on both foreground and background areas of an image, outline message blocks. In message extraction, a preprocessing step removes any white boarders, identifies the best defined corner of a message block, crops the image, and rotates the image to place the identified corner at the top-left corner. Message extraction scans the rotated image in window segments of increasing size during multiple cycles. During each cycle, if a bit pattern cannot be identified as a data bit, then the size of the examined bit area is increased and rechecked to see it specifically is a marker bit. If no bit information can be definitively identified, then it is assigned a logic bit value based on a 50% random assignment. | 08-11-2011 |
20110200269 | Fast Approximation For Bilateral Filter - Multiple filters of a bilateral filter are decoupled to form into multple linear filtering operations, which permits faster processing. The bilateral filter is re-presented as an approximate bilateral filter, and subjected to a logarithm whose resultant components are further subjected to a series of Jensen approximations. The errors resulting from each Jensen approximation are collected into a single cumulative error factor, and it is then shown that the cumulative error may be ignored without adversed affect to the result. Thus, the original bilateral filter may be implemented as log(y | 08-18-2011 |
20110243428 | Bi-Affinity Filter: A Bilateral Type Filter for Color Images - An edge preserving filter that works on the principle of matting affinity allows a better representation of the range filter term in bilateral class filters. The definition of the affinity term can be relaxed to suit different applications. An approximate bi-affinity filter whose output is shown to be very similar to the traditional bilateral filter is defined. The present technique has the added advantage that no color space changes are required and hence an input image can be handled in its original color space. This is a big benefit over the traditional bilateral filter, which needs conversion to perception based spaces, such as CIELAB, to generate results close to the present invention. The full bi-affinity filter preserves very minute details of the input image, and thus permits an enhanced zooming functionality. | 10-06-2011 |
20120008862 | Bi-Affinity Filter: A Bilateral Type Filter for Color Images - Application of an image filtering algorithm, which defines an algorithm window within which a center pixel is processed relative to the other pixels within the algorithm window, is improved by use of an extended window larger than and encompassing the algorithm window. This approached is applied with an edge preserving filter that works on the principle of matting affinity and allows a better representation of the range filter term in bilateral class filters. An approximate bi-affinity filter whose output is shown to be very similar to the traditional bilateral filter is defined. The present technique has the added advantage that no color space changes are required and hence an input image can be handled in its original color space. | 01-12-2012 |
20120041725 | Supervised Nonnegative Matrix Factorization - Graph embedding is incorporated into nonnegative matrix factorization, NMF, while using the original formulation of graph embedding. Negative values are permitted in the definition of graph embedding without violating the nonnegative requirement of NMF. The factorized matrices of NMF are found by an iterative process. | 02-16-2012 |
20120041905 | Supervised Nonnegative Matrix Factorization - Supervised nonnegative matrix factorization (SNMF) generates a descriptive part-based representation of data, based on the concept of nonnegative matrix factorization (NMF) aided by the discriminative concept of graph embedding. An iterative procedure that optimizes suggested formulation based on Pareto optimization is presented. The present formulation removes any dependence on combined optimization schemes. Analytical and empirical evidence is presented to show that SNMF has advantages over popular subspace learning techniques as well as current state-of-the-art techniques. | 02-16-2012 |
20120041906 | Supervised Nonnegative Matrix Factorization - Supervised kernel nonnegative matrix factorization generates a descriptive part-based representation of data, based on the concept of kernel nonnegative matrix factorization (kernel NMF) aided by the discriminative concept of graph embedding. An iterative procedure that optimizes suggested formulation based on Pareto optimization is presented. The present formulation removes any dependence on combined optimization schemes. | 02-16-2012 |