User Preference in Detail-Enhancement Adjustments for Images Captured by Camera Phones

Most smartphones now come with an integrated camera. Such a smartphone is called a camera phone. Popularity of camera phones is rising and it is expected that 87.8% of United States population will possess camera phones by year 2020 (Euromonitor International, 2017). A camera phone’s workflow for capturing, editing, and sharing images on social media has become very efficient. Its ease of use, accessibility, and automatic exposure settings to capture an image has contributed to its popularity. Camera phones are more compact and convenient than professional DSLR cameras. The popularity of this technology has created a need to study and evaluate image quality of photographs from the camera phone. Numerous image-editing applications and adjustments are available to edit these images on the phone itself. Previous studies have shown the reasons why people like to edit their images captured by camera phones (Bakhshi et al., 2014; Bakhshi et al., 2015). This psychophysical study aims to determine the preference related to detail-enhancement adjustments for images captured by camera phones. The image contents used in this study are selfies and food images. Images possessing two levels of high and low ISO were evaluated. The stimuli for the psychophysical experiment were created by editing these images with clarity, contrast and sharpness adjustments. By recording participants’ response and analyzing the data, observers’ preference were determined for different detail-enhancement (DE) adjustments and content of images captured by camera phones. Results showed that the preference for detail-enhancement adjustments was subjective and varied by both person and image. Participants preferred low ISO DE images more than high ISO DE images. Overall, only slight preferences were observed between images possessing different DE adjustments, DE levels and contents, but a significant preference was not observed in any of these variables

Subjective Image Quality Assessment of Digitally Printed Images

Smartphones have become ingrained in our daily activities, driving their cameras to become better with every generation. As more and more images are being taken by cell phones it has become increasingly important to assess the quality of the images taken by different phones. While many cell phone images are only viewed electronically, many images also get transformed into printed images, especially photo-books, as digital printing gets better and cheaper compared to traditional printing processes. The gap between electronic image and printed image in shrinking rapidly and it becomes important to study the transition of images from screen to paper. The main goal of this research was to perform a rank order experiment for assessing cell phone image capture quality that translates to printed images via several different digital printers. It was of interest to investigate whether the overall image quality on displays correlates well with printed image quality. The important aspect was to study was to observe if there is a loss of image quality due to different digital printers

Long Term use of Cell Phone in Business Community causing Hearing Loss

INTRODUCTION: As civilization has progressed, the noise in man‘s environment has increased. The adverse effect of noise is widespread with respect to human physiology and produce changes in many bio systems other than ear. It is however the ear which concerns us here. Noise has been shown to have many effects on people such as, decrease in working efficiency, annoyance, physiological changes in blood pressure and heart rate and psychological distress. The direct auditory effects are interference with speech communication, produced due to the masking background noise, and the primary auditory effect, the capacity of noise to produce hearing loss. AIM OF THE STUDY: Noise induced hearing loss is a preventable hearing disorder. It affects people of all ages and demographic. When increased intensity is transmitted into and through the auditory system noise induced hearing loss results. MATERIALS AND METHODOLOGY: Cross sectional study. N=90, Age group: 18-50 years. Year of study: 2010-2012. Inclusion criteria: 1. 18 – 50 years of age, 2. Healthy male vegetable traders, 3. Any type of mobile phones, 4. Normal intact tympanic membrane. Exclusion criteria: 1. Any history of any other co morbid illness like hypertension, diabetes mellitus, cardiac illness. 2. Any ear disease which have hearing loss 3. Any surgery to the ear with no improvement of hearing after surgery. 4. Any intake of ototoxic medications. SUMMARY: The cross sectional study was conducted from a period of November 2010 to October 2012, to study the effects of cellphone usage over the human auditory system. Total number of subjects – 90 healthy males. All the subjects were in the age group of 18 to 50 years. 37.78% (34 / 90) of subjects had ear warmth. 34.44% (31 / 90) of subjects had ear fullness. 8.88% (8 / 90) of subjects had tinnitus. Pure tone audiometry done periodically at the interval of one year from the baseline audiogram showing threshold changes in one or two frequencies in the follow up audiogram in 10% of the subjects. These candidates must be followed up regularly, for a long term to derive a final conclusion. CONCLUSION: In this study, on following up of 90 candidates for 3 years with pure tone audiometry, no significant hearing loss was observed, except some threshold changes in one or two frequencies in the final follow up audiogram. It is also observed, that the ear symptoms like ear warmth and ear fullness was observed in approximately 30% of subjects and there was no relation between the ear symptoms and threshold changes. Mild cochlear changes can be revealed in Distortion product otoacoustic emissions and auditory brainstem response. However this is a small cross sectional study, a large sample and long term follow up will be required to derive definite conclusions

A Study of Colour Rendering in the In-Camera Imaging Pipeline

Consumer cameras such as digital single-lens reflex camera (DSLR) and smartphone cameras have onboard hardware that applies a series of processing steps to transform the initial captured raw sensor image to the final output image that is provided to the user. These processing steps collectively make up the in-camera image processing pipeline. This dissertation aims to study the processing steps related to colour rendering which can be categorized into two stages. The first stage is to convert an image's sensor-specific raw colour space to a device-independent perceptual colour space. The second stage is to further process the image into a display-referred colour space and includes photo-finishing routines to make the image appear visually pleasing to a human. This dissertation makes four contributions towards the study of camera colour rendering. The first contribution is the development of a software-based research platform that closely emulates the in-camera image processing pipeline hardware. This platform allows the examination of the various image states of the captured image as it is processed from the sensor response to the final display output. Our second contribution is to demonstrate the advantage of having access to intermediate image states within the in-camera pipeline that provide more accurate colourimetric consistency among multiple cameras. Our third contribution is to analyze the current colourimetric method used by consumer cameras and to propose a modification that is able to improve its colour accuracy. Our fourth contribution is to describe how to customize a camera imaging pipeline using machine vision cameras to produce high-quality perceptual images for dermatological applications. The dissertation concludes with a summary and future directions

Safe Driving using Vision-based Hand Gesture Recognition System in Non-uniform Illumination Conditions

Nowadays, there is tremendous growth in in-car interfaces for driver safety and comfort, but controlling these devices while driving requires the driver's attention. One of the solutions to reduce the number of glances at these interfaces is to design an advanced driver assistance system (ADAS). A vision-based touch-less hand gesture recognition system is proposed here for in-car human-machine interfaces (HMI). The performance of such systems is unreliable under ambient illumination conditions, which change during the course of the day. Thus, the main focus of this work was to design a system that is robust towards changing lighting conditions. For this purpose, a homomorphic filter with adaptive thresholding binarization is used. Also, gray-level edge-based segmentation ensures that it is generalized for users of different skin tones and background colors. This work was validated on selected gestures from the Cambridge Hand Gesture Database captured in five sets of non-uniform illumination conditions that closely resemble in-car illumination conditions, yielding an overall system accuracy of 91%, an average frame-by-frame accuracy of 81.38%, and a latency of 3.78 milliseconds. A prototype of the proposed system was implemented on a Raspberry Pi 3 interface together with an Android application, which demonstrated its suitability for non-critical in-car interfaces like infotainment systems

A Practitioner Survey Exploring the Value of Forensic Tools, AI, Filtering, & Safer Presentation for Investigating Child Sexual Abuse Material

For those investigating cases of Child Sexual Abuse Material (CSAM), there is the potential harm of experiencing trauma after illicit content exposure over a period of time. Research has shown that those working on such cases can experience psychological distress. As a result, there has been a greater effort to create and implement technologies that reduce exposure to CSAM. However, not much work has explored gathering insight regarding the functionality, effectiveness, accuracy, and importance of digital forensic tools and data science technologies from practitioners who use them. This study focused specifically on examining the value practitioners give to the tools and technologies they utilize to investigate CSAM cases. General findings indicated that implementing filtering technologies is more important than safe-viewing technologies; false positives are a greater concern than false negatives; resources such as time, personnel, and money continue to be a concern; and an improved workflow is highly desirable. Results also showed that practitioners are not well-versed in data science and Artificial Intelligence (AI), which is alarming given that tools already implement these techniques and that practitioners face large amounts of data during investigations. Finally, the data exemplified that practitioners are generally not taking advantage of tools that implement data science techniques, and that the biggest need for them is in automated child nudity detection, age estimation and skin tone detection

Integration of biometrics and steganography: A comprehensive review

The use of an individual’s biometric characteristics to advance authentication and verification technology beyond the current dependence on passwords has been the subject of extensive research for some time. Since such physical characteristics cannot be hidden from the public eye, the security of digitised biometric data becomes paramount to avoid the risk of substitution or replay attacks. Biometric systems have readily embraced cryptography to encrypt the data extracted from the scanning of anatomical features. Significant amounts of research have also gone into the integration of biometrics with steganography to add a layer to the defence-in-depth security model, and this has the potential to augment both access control parameters and the secure transmission of sensitive biometric data. However, despite these efforts, the amalgamation of biometric and steganographic methods has failed to transition from the research lab into real-world applications. In light of this review of both academic and industry literature, we suggest that future research should focus on identifying an acceptable level steganographic embedding for biometric applications, securing exchange of steganography keys, identifying and address legal implications, and developing industry standards