ORGB: Offset Correction in RGB Color Space for Illumination-Robust Image Processing

Single materials have colors which form straight lines in RGB space. However, in severe shadow cases, those lines do not intersect the origin, which is inconsistent with the description of most literature. This paper is concerned with the detection and correction of the offset between the intersection and origin. First, we analyze the reason for forming that offset via an optical imaging model. Second, we present a simple and effective way to detect and remove the offset. The resulting images, named ORGB, have almost the same appearance as the original RGB images while are more illumination-robust for color space conversion. Besides, image processing using ORGB instead of RGB is free from the interference of shadows. Finally, the proposed offset correction method is applied to road detection task, improving the performance both in quantitative and qualitative evaluations.Comment: Project website: https://baidut.github.io/ORGB

On the aeroacoustic and flow structures developed on a flat plate with a serrated sawtooth trailing edge

Open Access funded by Engineering and Physical Sciences Research Council.Results of an experimental study on turbulent flow over a flat plate with a serrated sawtooth trailing edge are presented in this paper. After tripping the boundary layer to become turbulent, the broadband noise sources at the sawtooth serrated trailing edge is studied by several experimental techniques. Broadband noise reduction by the serrated sawtooth trailing edge can be realistically achieved in the flat plate configuration. The variations of wall pressure power spectral density and the spanwise coherence (which relates to the spanwise correlation length) in a sawtooth trailing edge play a minor role in the mechanisms underpinning the reduction of self noise radiation. Conditional-averaging technique was applied in the boundary layer data where a pair of pressure-driven oblique vortical structures near the sawtooth side edges is identified. In the current flat plate configuration, the interaction between the vortical structures and the local turbulent boundary layer results in a redistribution of the momentum transport and turbulent shear stress near the sawtooth side edges as well as the sawtooth tip, thus affecting the efficiency of self noise radiation.The authors are grateful for the support from the EPSRC Doctoral Training Grants in the United Kingdom

Automatic Lesser Kestrel’s Gender Identification using Video Processing

Traditionally, animal surveillance is a common task for biologists. However, this task is often accompanied by the inspection of huge amounts of video. In this sense, this paper proposes an automatic video processing algorithm to identify the gender of a kestrel species. It is based on optical flow and texture analysis. This algorithm makes it possible to identify the important information and therefore, minimizing the analysis time for biologists. Finally, to validate this algorithm, it has been tested against a set of videos, getting good classification results.Junta de Andalucía P10-TIC-570

Implementation of target tracking in Smart Wheelchair Component System

Independent mobility is critical to individuals of any age. While the needs of many individuals with disabilities can be satisfied with power wheelchairs, some members of the disabled community find it difficult or impossible to operate a standard power wheelchair. This population includes, but is not limited to, individuals with low vision, visual field neglect, spasticity, tremors, or cognitive deficits. To meet the needs of this population, our group is involved in developing cost effective modularly designed Smart Wheelchairs. Our objective is to develop an assistive navigation system which will seamlessly integrate into the lifestyle of individual with disabilities and provide safe and independent mobility and navigation without imposing an excessive physical or cognitive load. The Smart Wheelchair Component System (SWCS) can be added to a variety of commercial power wheelchairs with minimal modification to provide navigation assistance. Previous versions of the SWCS used acoustic and infrared rangefinders to identify and avoid obstacles, but these sensors do not lend themselves to many desirable higher-level behaviors. To achieve these higher level behaviors we integrated a Continuously Adapted Mean Shift (CAMSHIFT) target tracking algorithm into the SWCS, along with the Minimal Vector Field Histogram (MVFH) obstacle avoidance algorithm. The target tracking algorithm provides the basis for two distinct operating modes: (1) a "follow-the-leader" mode, and (2) a "move to stationary target" mode.The ability to track a stationary or moving target will make smart wheelchairs more useful as a mobility aid, and is also expected to be useful for wheeled mobility training and evaluation. In addition to wheelchair users, the caregivers, clinicians, and transporters who provide assistance to wheelchair users will also realize beneficial effects of providing safe and independent mobility to wheelchair users which will reduce the level of assistance needed by wheelchair users

De-velopment of Demosaicking Techniques for Multi-Spectral Imaging Using Mosaic Focal Plane Arrays

The use of mosaicked array technology in commercial digital cameras has madethem smaller, cheaper and mechanically more robust. In a mosaicked sensor, each pixel detector is covered with a wavelength-specific optical filter. Since only one spectral band is sensed per pixel location, there is an absence of information from the rest of the spectral bands. These unmeasured spectral bands are estimated by using information obtained from the neighborhood pixels. This process of estimating the unmeasured spectral band information is called demosaicking. The demosaicking process uses interpolation strategies to estimate the missing pixels. Sophisticated interpolation methods have been developed for performing this task in digital color cameras.In this thesis we propose to evaluate the adaptation of the mosaicked technol- ogy for multi-spectral cameras. Existing multi-spectral cameras use traditional methods like imaging spectrometers to capture a multi-spectral image. These methods are very expensive and delicate in nature. The objective of using the mosaicked technology for multi-spectral cameras is to reap the same benefits it offers in the commercial digital color cameras. However, the problem in using the mosaicked technology for multi-spectral images is the huge amount of missing pixels that need to be estimated in order to form the multi-spectral image. The estimation process becomes even more complicated as the number of bands in the multi-spectral image increases. Traditional demosaicking algorithms cannot be used because they have been specifically designed to suit three-band color images.This thesis focuses on developing new demosaicking algorithms for multi- spectral images. The existing demosaicking algorithms for color images have been extended for multi-spectral images. A new variation of the bilinear interpolationbased strategy has been developed to perform demosaicking. This demosaicking method uses variable neighborhood definitions to interpolate the missing spectral band values at each pixel locations in a multi-spectral image. A novel Maximum a-Posteriori (MAP) based demosaicking method has also been developed. This method treats demosaicking as an image restoration problem. It can derive op- timal estimation result that resembles the original image the best. In addition, it can simultaneously perform interpolation of missing spectral bands at pixel locations and also remove noise and degradations in the image.Extensive experimentation and comparisons have shown that the new demo- saicking methods for multi-spectral images developed in this thesis perform better than the traditional interpolation trategies. The outputs from the demosaicking methods have been shown to be better reconstructed estimates of the original im- ages and also have the ability to produce good classification results in applicationslike target recognition and discrimination

Object Tracking in Distributed Video Networks Using Multi-Dimentional Signatures

From being an expensive toy in the hands of governmental agencies, computers have evolved a long way from the huge vacuum tube-based machines to today\u27s small but more than thousand times powerful personal computers. Computers have long been investigated as the foundation for an artificial vision system. The computer vision discipline has seen a rapid development over the past few decades from rudimentary motion detection systems to complex modekbased object motion analyzing algorithms. Our work is one such improvement over previous algorithms developed for the purpose of object motion analysis in video feeds. Our work is based on the principle of multi-dimensional object signatures. Object signatures are constructed from individual attributes extracted through video processing. While past work has proceeded on similar lines, the lack of a comprehensive object definition model severely restricts the application of such algorithms to controlled situations. In conditions with varying external factors, such algorithms perform less efficiently due to inherent assumptions of constancy of attribute values. Our approach assumes a variable environment where the attribute values recorded of an object are deemed prone to variability. The variations in the accuracy in object attribute values has been addressed by incorporating weights for each attribute that vary according to local conditions at a sensor location. This ensures that attribute values with higher accuracy can be accorded more credibility in the object matching process. Variations in attribute values (such as surface color of the object) were also addressed by means of applying error corrections such as shadow elimination from the detected object profile. Experiments were conducted to verify our hypothesis. The results established the validity of our approach as higher matching accuracy was obtained with our multi-dimensional approach than with a single-attribute based comparison

Digital Color Imaging

This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided