Cell phones and other portable devices are equipped with a variety of technologies by which existing functionality can be improved, and new functionality can be provided. Some relate to visual search capabilities, and determining appropriate actions responsive to different image inputs. Others relate to processing of image data. Still others concern metadata generation, processing, and representation. Yet others relate to coping with fixed focus limitations of cell phone cameras, e.g., in reading digital watermark data. Still others concern user interface improvements. A great number of other features and arrangements are also detailed.

Methods and Systems for Content Processing

Mathematical and computational modeling of genetic regulatory networks promises to uncover the fundamental principles governing biological systems in an integrative and holistic manner. It also paves the way toward the development of systematic approaches for effective therapeutic intervention in disease. The central theme in this paper is the Boolean formalism as a building block for modeling complex, large-scale, and dynamical networks of genetic interactions. We discuss the goals of modeling genetic networks as well as the data requirements. The Boolean formalism is justified from several points of view. We then introduce Boolean networks and discuss their relationships to nonlinear digital filters. The role of Boolean networks in understanding cell differentiation and cellular functional states is discussed. The inference of Boolean networks from real gene expression data is considered from the viewpoints of computational learning theory and nonlinear signal processing, touching on computational complexity of learning and robustness. Then, a discussion of the need to handle uncertainty in a probabilistic framework is presented, leading to an introduction of probabilistic Boolean networks and their relationships to Markov chains. Methods for quantifying the influence of genes on other genes are presented. The general question of the potential effect of individual genes on the global dynamical network behavior is considered using stochastic perturbation analysis. This discussion then leads into the problem of target identification for therapeutic intervention via the development of several computational tools based on first-passage times in Markov chains. Examples from biology are presented throughout the paper.

From Boolean to probabilistic Boolean networks as models of genetic regulatory networks

A compact and efficient algorithm for digital envelope detection in white light interferograms is derived from a well-known phase-shifting algorithm. The performance of the new algorithm is compared with that of other schemes currently used. Principal criteria considered are computational efficiency and accuracy in the presence of miscalibration. The new algorithm is shown to be near optimal in terms of computational efficiency and can be represented as a second-order nonlinear filter. In combination with a carefully designed peak detection method the algorithm exhibits exceptionally good performance on simulated interferograms.

https://nontrivialzeros.net/KGL_Papers/23_Neat_Algorithm_JOSAA96.pdf

Efficient nonlinear algorithm for envelope detection in white light interferometry

A survey of recent advances in CNN-based single image crowd counting and density estimation

A bistable electro-optic display has a plurality of pixels, each of which is capable of displaying at least three gray levels. The display is driven by a method comprising: storing a look-up table containing data representing the impulses necessary to convert an initial gray level to a final gray level; storing data representing at least an initial state of each pixel of the display; receiving an input signal representing a desired final state of at least one pixel of the display; and generating an output signal representing the impulse necessary to convert the initial state of said one pixel to the desired final state thereof, as determined from said look-up table. The invention also provides a method for reducing the remnant voltage of an electro-optic display.

Methods for driving bistable electro-optic displays, and apparatus for use therein

A method and apparatus for automating the design of morphological or template-based filters for print quality enhancement. A plurality of different phase, but same resolution, subsampled images are generated from training documents. Statistical data derived therefrom is then employed in an automated process to generate filters. The filters may be used for resolution enhancement and/or conversion of bitmap images. Furthermore, the statistical data is used to produce filters that are intended to not only optimize image structure, but image density as well.

Image resolution conversion method that employs statistically generated multiple morphological filters

The hit-or-miss operator is used as the building block of optimal binary restoration filters. Filter design methodologies are given for general-, maximum-, and minimum-noise environments, the latter two producing optimal thinning and thickening filters, respectively, and for iterative filters. The approach is based on the expression of translation-invariant filters as unions of hit-or-miss transforms. Unions of hit-or-miss transforms are expressed as canonical logical sums of products, and the final hit-or-miss templates are obtained by logic reduction. The net effect is a morphological representation and estimation of the conditional expectation, which is the overall optimal mean-absolute-error filter.

Optimal mean-absolute-error hit-or-miss filters: morphological representation and estimation of the binary conditional expectation

For both the binary and gray scales, mean square optimal digital morphological filters have been characterized previously in terms of the Matheron erosion representation for increasing, translation-invariant mappings. Included in the characterization is the minimal search strategy for the optimal filter basis; however, without prior statistical information or an adequate image-noise model, even in the binary setting, filter design is computationally intractable for moderately sized observation windows. The mitigation of the computational burden via design constraints is the focus here. Although the resulting filter will be suboptimal, if the constraints are imposed in a suitable manner, little loss of filter performance occurs in return for design tractability. Three approaches are considered: limiting the number of terms in the Matheron expansion, constraining the observation window, and employing structuring element libraries. In the latter methodology various sublibraries are formed and a suboptimal filter is derived from image-noise statistics in conjunction with a basis search restricted to relevant sublibraries. This study analyzes two techniques for library construction: the expert approach involves prior sublibrary formation based on knowledge of important filter bases and the first-order approach employs single-erosion statistical information to limit the basis search to likely useful candidates.

Facilitation of optimal binary morphological filter design via structuring element libraries and design constraints

This volume addresses the field of digital document enhancement and restoration as it is implemented in these settings. Among the areas covered are the language and working definitions of the field, current industry practices, the document image class, logic-based image processing within that setting, and algorithms for performing enhancement and restoration of digital documents.

Enhancement and Restoration of Digital Documents: Statistical Design of Nonlinear Algorithms

Described herein is a method of determining parking lot occupancy from digital images, including a set-up procedure that includes receiving a layout of a parking lot and estimating parking space volume for at least one viewing angle and the probability that an observed pixel belongs to the parking space volume. The method further includes acquiring one or more image frames of the parking lot from at least one digital camera; performing pixel classification using a vehicle detector on the acquired image frames to determine a likelihood that a pixel belongs to a vehicle; computing a probability that a parking space is occupied by a vehicle based on a spatially varying membership probability density function and a likelihood of vehicle pixels within a region of interest; and determining parking lot vacancy via a comparison of the computed probability that a parking space is occupied by a vehicle to a pre-determined threshold.

Robert P. Loce

Papers

Image resolution conversion method that employs statistically generated multiple morphological filters

Optimal mean-absolute-error hit-or-miss filters: morphological representation and estimation of the binary conditional expectation

Facilitation of optimal binary morphological filter design via structuring element libraries and design constraints

Enhancement and Restoration of Digital Documents: Statistical Design of Nonlinear Algorithms

Method of determining parking lot occupancy from digital camera images