Advances on CMOS image sensors

This paper offers an introduction to the technological advances of image sensors designed using complementary metal–oxide–semiconductor (CMOS) processes along the last decades. We review some of those technological advances and examine potential disruptive growth directions for CMOS image sensors and proposed ways to achieve them. Those advances include breakthroughs on image quality such as resolution, capture speed, light sensitivity and color detection and advances on the computational imaging. The current trend is to push the innovation efforts even further as the market requires higher resolution, higher speed, lower power consumption and, mainly, lower cost sensors. Although CMOS image sensors are currently used in several different applications from consumer to defense to medical diagnosis, product differentiation is becoming both a requirement and a difficult goal for any image sensor manufacturer. The unique properties of CMOS process allows the integration of several signal processing techniques and are driving the impressive advancement of the computational imaging. With this paper, we offer a very comprehensive review of methods, techniques, designs and fabrication of CMOS image sensors that have impacted or might will impact the images sensor applications and markets

Offline Handwritten Signature Verification - Literature Review

The area of Handwritten Signature Verification has been broadly researched in the last decades, but remains an open research problem. The objective of signature verification systems is to discriminate if a given signature is genuine (produced by the claimed individual), or a forgery (produced by an impostor). This has demonstrated to be a challenging task, in particular in the offline (static) scenario, that uses images of scanned signatures, where the dynamic information about the signing process is not available. Many advancements have been proposed in the literature in the last 5-10 years, most notably the application of Deep Learning methods to learn feature representations from signature images. In this paper, we present how the problem has been handled in the past few decades, analyze the recent advancements in the field, and the potential directions for future research.Comment: Accepted to the International Conference on Image Processing Theory, Tools and Applications (IPTA 2017

Mach Bands: How Many Models are Possible? Recent Experiemental Findings and Modeling Attempts

Mach bands are illusory bright and dark bands seen where a luminance plateau meets a ramp, as in half-shadows or penumbras. A tremendous amount of work has been devoted to studying the psychophysics and the potential underlying neural circuitry concerning this phenomenon. A number of theoretical models have also been proposed, originating in the seminal studies of Mach himself. The present article reviews the main experimental findings after 1965 and the main recent theories of early vision that have attempted to discount for the effect. It is shown that the different theories share working principles and can be grouped in three clsses: a) feature-based; b) rule-based; and c) filling-in. In order to evaluate individual proposals it is necessary to consider them in the larger picture of visual science and to determine how they contribute to the understanding of vision in general.Air Force Office of Scientific Research (F49620-92-J-0334); Office of Naval Research (N00014-J-4100); COPPE/UFRJ, Brazi

Mach Band Attenuation by Adjacent Stimuli

Mach bands are illusory bright and dark bands seen where a luminance plateau meets a ramp, as in half-shadows or penumbras. Ratliff, Milkman, and Kaufman (1983) showed that Mach bands are attenuated by placing stimuli, such as bars, nearby. An experiment comparing Mach band attenuation for bar and Craik-O'Brien stimuli shows that they are equally effective in attenuating Mach bands. The results suggest that the high-frequency components of a stimulus adjacent to a ramp are responsible for the attenuation. Thc findings are interpreted in terms of a recent filling-in model of brighness perception and the results of computer simulations of stimuli used by Ratliff et al and the present experiment are shown