A survey of visual preprocessing and shape representation techniques

Many recent theories and methods proposed for visual preprocessing and shape representation are summarized. The survey brings together research from the fields of biology, psychology, computer science, electrical engineering, and most recently, neural networks. It was motivated by the need to preprocess images for a sparse distributed memory (SDM), but the techniques presented may also prove useful for applying other associative memories to visual pattern recognition. The material of this survey is divided into three sections: an overview of biological visual processing; methods of preprocessing (extracting parts of shape, texture, motion, and depth); and shape representation and recognition (form invariance, primitives and structural descriptions, and theories of attention)

A Human Visual System Inspired Feature Recognition Method Using Convolutional Neural Networks

While significant strides in neural network and machine vision applications have been made in recent years, humans still remain the most proficient at feature extraction and pattern recognition tasks. Some researchers have attempted to utilize select aspects of the human visual system in order to perform application-specific visual tasks. However, none have been able to develop a computational model of the biological human visual system that can perform the many complex pattern recognition tasks that we do as humans. This thesis focuses on significant improvements to an existing human visual system model created by N. Radhi, and the novel implementation of a deep learning system for road detection utilizing non-uniformly sampled images in log-polar coordinate space. A convolutional neural network is used to compare the non-uniformly sampled image model with the conventional uniform structure, with the non-uniform model demonstrating significant increases in processing speed while retaining high validation accuracy. Comparisons between the uniform and non-uniform models when subjected to a variety of preprocessing methods are presented

VETA-I x ray test analysis

This interim report presents some definitive results from our analysis of the VETA-I x-ray testing data. It also provides a description of the hardware and software used in the conduct of the VETA-I x-ray test program performed at the MSFC x-ray Calibration Facility (XRCF). These test results also serve to supply data and information to include in the TRW final report required by DPD 692, DR XC04. To provide an authoritative compendium of results, we have taken nine papers as published in the SPIE Symposium, 'Grazing Incidence X-ray/EUV Optics for Astronomy and Projection Lithography' and have reproduced them as the content of this report

Symmetry-breaking phase-transitions in highly concentrated semen

New experimental evidence of self-motion of a confined active suspension is presented. Depositing fresh semen sample in an annular shaped micro- fluidic chip leads to a spontaneous vortex state of the fluid at sufficiently large sperm concentration. The rotation occurs unpredictably clockwise or counterclockwise and is robust and stable. Furthermore, for highly active and concentrated semen, richer dynamics can occur such as self-sustained or damped rotation oscillations. Experimental results obtained with systematic dilution provide a clear evidence of a phase transition toward collective motion associated with local alignment of spermatozoa akin to the Vicsek model. A macroscopic theory based on previously derived Self-Organized Hydrodynamics (SOH) models is adapted to this context and provides predictions consistent with the observed stationary motion

A retinal code for motion along the gravitational and body axes

Self-motion triggers complementary visual and vestibular reflexes supporting image-stabilization and balance. Translation through space produces one global pattern of retinal image motion (optic flow), rotation another. We examined the direction preferences of direction-sensitive ganglion cells (DSGCs) in flattened mouse retinas in vitro. Here we show that for each subtype of DSGC, direction preference varies topographically so as to align with specific translatory optic flow fields, creating a neural ensemble tuned for a specific direction of motion through space. Four cardinal translatory directions are represented, aligned with two axes of high adaptive relevance: the body and gravitational axes. One subtype maximizes its output when the mouse advances, others when it retreats, rises or falls. Two classes of DSGCs, namely, ON-DSGCs and ON-OFF-DSGCs, share the same spatial geometry but weight the four channels differently. Each subtype ensemble is also tuned for rotation. The relative activation of DSGC channels uniquely encodes every translation and rotation. Although retinal and vestibular systems both encode translatory and rotatory self-motion, their coordinate systems differ

Retinal Fundus Image Analysis for Diagnosis of Glaucoma: A Comprehensive Survey

© 2016 IEEE. The rapid development of digital imaging and computer vision has increased the potential of using the image processing technologies in ophthalmology. Image processing systems are used in standard clinical practices with the development of medical diagnostic systems. The retinal images provide vital information about the health of the sensory part of the visual system. Retinal diseases, such as glaucoma, diabetic retinopathy, age-related macular degeneration, Stargardt's disease, and retinopathy of prematurity, can lead to blindness manifest as artifacts in the retinal image. An automated system can be used for offering standardized large-scale screening at a lower cost, which may reduce human errors, provide services to remote areas, as well as free from observer bias and fatigue. Treatment for retinal diseases is available; the challenge lies in finding a cost-effective approach with high sensitivity and specificity that can be applied to large populations in a timely manner to identify those who are at risk at the early stages of the disease. The progress of the glaucoma disease is very often quiet in the early stages. The number of people affected has been increasing and patients are seldom aware of the disease, which can cause delay in the treatment. A review of how computer-aided approaches may be applied in the diagnosis and staging of glaucoma is discussed here. The current status of the computer technology is reviewed, covering localization and segmentation of the optic nerve head, pixel level glaucomatic changes, diagonosis using 3-D data sets, and artificial neural networks for detecting the progression of the glaucoma disease

Recognition of License Plates and Optical Nerve Pattern Detection Using Hough Transform

The global technique of detection of the features is Hough transform used in image processing, computer vision and image analysis. The detection of prominent line of the object under consideration is the main purpose of the Hough transform which is carried out by the process of voting. The first part of this work is the use of Hough transform as feature vector, tested on Indian license plate system, having font of UK standard and UK standard 3D, which has ten slots for characters and numbers.So tensub images are obtained.These sub images are fed to Hough transform and Hough peaks to extract the Hough peaks information. First two Hough peaks are taken into account for the recognition purposes. The edge detection along with image rotation is also used prior to the implementation of Hough transform in order to get the edges of the gray scale image. Further, the image rotation angle is varied; the superior results are taken under consideration. The second part of this work makes the use of Hough transform and Hough peaks, for examining the optical nerve patterns of eye. An available database for RIM-one is used to serve the purpose. The optical nerve pattern is unique for every human being and remains almost unchanged throughout the life time. So the purpose is to detect the change in the pattern report the abnormality, to make automatic system so capable that they can replace the experts of that field. For this detection purpose Hough Transform and Hough Peaks are used and the fact that these nerve patterns are unique in every sense is confirmed