Good vision is more than 20/20 on a Snellen visual acuity chart. The modern ophthalmologist understands that contrast sensitivity, near and distance vision, performance under light and dark conditions, and the brain's interpretation of input from the sensory apparatus, are all important elements in patients' quality of vision. In Quality of Vision: Essential Optics for the Ophthalmic Surgeon, ophthalmologist and optics expert Dr. Jack T. Holladay explores the elements of vision that lie beyond Snellen testing. He explains the Quality of Vision addresses: - Measuring and treating astigmatism in corneal and IOL surgery - The importance of correcting spherical aberration in cataract and refractive surgery - IOL calculations after refractive surgery - Promising approaches to the correction of presbyopia - Other practical topics the clinician can use every day Recognized as the leader in ophthalmic optics, Dr. Holladay incorporates practical aspects of daily practice into each chapter as he expertly explains the scientific principles, mathematical formulas, and theories behind these important issues. Additionally, Quality of Vision includes numerous color illustrations to provide visual representations of the text's key points. Dr. Holladay discusses what's on everyone's mind: - How to take the best measurements and perform the best calculations to ensure good outcomes in cataract and refractive surgery - How neural adaptation can improve outcomes - How today's excimer laser systems deliver excellent optical correction, and why tomorrow's systems will perform even better Quality of Vision: Essential Optics for the Ophthalmic Surgeon is the most complete and practical reference for ophthalmologists looking to increase their understanding of optical physics and their ability to deliver good vision to their patients after cataract and refractive surgery.

The ability to see deeply affects how human beings perceive and interpret the world around them. For most people, eyesight is part of everyday communication, social activities, educational and professional pursuits, the care of others, and the maintenance of personal health, independence, and mobility. Functioning eyes and vision system can reduce an adult's risk of chronic health conditions, death, falls and injuries, social isolation, depression, and other psychological problems. In children, properly maintained eye and vision health contributes to a child's social development, academic achievement, and better health across the lifespan. The public generally recognizes its reliance on sight and fears its loss, but emphasis on eye and vision health, in general, has not been integrated into daily life to the same extent as other health promotion activities, such as teeth brushing; hand washing; physical and mental exercise; and various injury prevention behaviors. A larger population health approach is needed to engage a wide range of stakeholders in coordinated efforts that can sustain the scope of behavior change. The shaping of socioeconomic environments can eventually lead to new social norms that promote eye and vision health. Making Eye Health a Population Health Imperative: Vision for Tomorrow proposes a new population-centered framework to guide action and coordination among various, and sometimes competing, stakeholders in pursuit of improved eye and vision health and health equity in the United States. Building on the momentum of previous public health efforts, this report also introduces a model for action that highlights different levels of prevention activities across a range of stakeholders and provides specific examples of how population health strategies can be translated into cohesive areas for action at federal, state, and local levels.

The first book in this rapidly expanding area, Computer Vision Technology for Food Quality Evaluation thoroughly discusses the latest advances in image processing and analysis. Computer vision has attracted much research and development attention in recent years and, as a result, significant scientific and technological advances have been made in quality inspection, classification and evaluation of a wide range of food and agricultural products. This unique work provides engineers and technologists working in research, development, and operations in the food industry with critical, comprehensive and readily accessible information on the art and science of computer vision technology. Undergraduate and postgraduate students and researchers in universities and research institutions will also find this an essential reference source.· Discusses novel technology for recognizing objects and extracting quantitative information from digital images in order to provide objective, rapid, non-contact and non-destructive quality evaluation. · International authors with both academic and professional credentials address in detail one aspect of the relevant technology per chapter making this ideal for textbook use· Divided into three parts, it begins with an outline of the fundamentals of the technology, followed by full coverage of the application in the most researched areas of meats and other foods, fruits, vegetables and grains.

When children and adults apply for disability benefits and claim that a visual impairment has limited their ability to function, the U.S. Social Security Administration (SSA) is required to determine their eligibility. To ensure that these determinations are made fairly and consistently, SSA has developed criteria for eligibility and a process for assessing each claimant against the criteria. Visual Impairments: Determining Eligibility for Social Security Benefits examines SSA's methods of determining disability for people with visual impairments, recommends changes that could be made now to improve the process and the outcomes, and identifies research needed to develop improved methods for the future. The report assesses tests of visual function, including visual acuity and visual fields whether visual impairments could be measured directly through visual task performance or other means of assessing disability. These other means include job analysis databases, which include information on the importance of vision to job tasks or skills, and measures of health-related quality of life, which take a person-centered approach to assessing visual function testing of infants and children, which differs in important ways from standard adult tests.

Machine Vision systems combine image processing with industrial automation. One of the primary areas of application of Machine Vision in the Industry is in the area of Quality Control. Machine vision provides fast, economic and reliable inspection that improves quality as well as business productivity. Building machine vision applications is a challenging task as each application is unique, with its own requirements and desired outcome. A Guide to Machine Vision in Quality Control follows a practitioner’s approach to learning machine vision. The book provides guidance on how to build machine vision systems for quality inspections. Practical applications from the Industry have been discussed to provide a good understanding of usage of machine vision for quality control. Real-world case studies have been used to explain the process of building machine vision solutions. The book offers comprehensive coverage of the essential topics, that includes: Introduction to Machine Vision Fundamentals of Digital Images Discussion of various machine vision system components Digital image processing related to quality control Overview of automation The book can be used by students and academics, as well as by industry professionals, to understand the fundamentals of machine vision. Updates to the on-going technological innovations have been provided with a discussion on emerging trends in machine vision and smart factories of the future. Sheila Anand is a PhD graduate and Professor at Rajalakshmi Engineering College, Chennai, India. She has over three decades of experience in teaching, consultancy and research. She has worked in the software industry and has extensive experience in development of software applications and in systems audit of financial, manufacturing and trading organizations. She guides Ph.D. aspirants and many of her research scholars have since been awarded their doctoral degree. She has published many papers in national and international journals and is a reviewer for several journals of repute. L Priya is a PhD graduate working as Associate Professor and Head, Department of Information Technology at Rajalakshmi Engineering College, Chennai, India. She has nearly two decades of teaching experience and good exposure to consultancy and research. She has delivered many invited talks, presented papers and won several paper awards in International Conferences. She has published several papers in International journals and is a reviewer for SCI indexed journals. Her areas of interest include Machine Vision, Wireless Communication and Machine Learning.