A novel method to count the red blood cells in thin blood films

This paper describes a novel idea to identify the total number of red blood cells (RBCs) as well as their location in a Giemsa stained thin blood film image. This work is being undertaken as a part of developing an automated malaria parasite detection system by scanning a photograph of thin blood film in order to evaluate the parasitemia of the blood. Not only will this method eliminates the segmentation procedures that are normally used to segment the cells in the microscopic image, but also avoids any image pre-processing to deal with non uniform illumination prior to cell detection. The method utilizes basic knowledge on cell structure and brightness of the components due to Giemsa staining of the sample and detects and locates the RBCs in the image.

A Fuzzy-Wavelet Neural Network Model for the Detection of Meat Spoilage using an Electronic Nose

Food product safety is one of the most promising areas for the application of electronic noses. The performance of a portable electronic nose has been evaluated in monitoring the spoilage of beef fillet stored aerobically at different storage temperatures (0, 4, 8, 12, 16 and 20°C). This paper proposes a fuzzy-wavelet neural network model which incorporates a clustering pre-processing stage for the definition of fuzzy rules. The dual purpose of the proposed modeling approach is not only to classify beef samples in the respective quality class (i.e. fresh, semi-fresh and spoiled), but also to predict their associated microbiological population directly from volatile compounds fingerprints. Comparison results indicated that the proposed modeling scheme could be considered as a valuable detection methodology in food microbiology

A Rapid Detection of Meat Spoilage using an Electronic Nose and Fuzzy-Wavelet systems

Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. To address the rapid detection of meat spoilage microorganisms during aerobic or modified atmosphere storage, an electronic nose with the aid of fuzzy wavelet network has been considered in this research. The proposed model incorporates a clustering pre-processing stage for the definition of fuzzy rules. The dual purpose of the proposed modelling approach is not only to classify beef samples in the respective quality class (i.e. fresh, semi-fresh and spoiled), but also to predict their associated microbiological population directly from volatile compounds fingerprints. Comparison results against neural networks and neurofuzzy systems indicated that the proposed modelling scheme could be considered as a valuable detection methodology in food microbiology

Image, video and 3D data registration: medical, satellite and video processing applications with quality metrics

Data registration refers to a series of techniques for matching or bringing similar objects or datasets together into alignment. These techniques enjoy widespread use in a diverse variety of applications, such as video coding, tracking, object and face detection and recognition, surveillance and satellite imaging, medical image analysis and structure from motion. Registration methods are as numerous as their manifold uses, from pixel level and block or feature based methods to Fourier domain methods. This book is focused on providing algorithms and image and video techniques for registration and quality performance metrics. The authors provide various assessment metrics for measuring registration quality alongside analyses of registration techniques, introducing and explaining both familiar and state–of–the–art registration methodologies used in a variety of targeted applications.

Adaptive self-calibrating image rejection receiver

An adaptive self-calibrating image rejection receiver is described, containing a modified Weaver image rejection mixer and a Digital Image Rejection Processor (DIRP). The blind source-separation-based DIRP eliminates the I/Q errors improving the Image Rejection Ratio (IRR) without the need for trimming or use of power-hungry discrete components. Hardware complexity is minimal, requiring only two complex coefficients; hence it can be easily integrated into the signal processing path of any receiver. Simulation results show that the proposed approach achieves 75-97 dB of IRR.

Identification of image attributes that are most affected with changes in displayed image size

This paper describes an investigation of changes in image appearance when images are viewed at different image sizes on a high-end LCD device. Two digital image capturing devices of different overall image quality were used for recording identical natural scenes with a variety of pictorial contents. From each capturing device, a total of sixty four captured scenes, including architecture, nature, portraits, still and moving objects and artworks under various illumination conditions and recorded noise level were selected. The test set included some images where camera shake was purposefully introduced. An achromatic version of the image set that contained only lightness information was obtained by processing the captured images in CIELAB space. Rank order experiments were carried out to determine which image attribute(s) were most affected when the displayed image size was altered. These evaluations were carried out for both chromatic and achromatic versions of the stimuli. For the achromatic stimuli, attributes such as contrast, brightness, sharpness and noisiness were rank-ordered by the observers in terms of the degree of change. The same attributes, as well as hue and colourfulness, were investigated for the chromatic versions of the stimuli. Results showed that sharpness and contrast were the two most affected attributes with changes in displayed image size. The ranking of the remaining attributes varied with image content and illumination conditions. Further, experiments were carried out to link original scene content to the attributes that changed mostly with changes in image size.

An exploration of pre-attentive visual discrimination using event-related potentials

The Mismatch Negativity (MMN) has been characterised as a ‘pre-attentive’ component of an Event-Related Potential (ERP) that is related to discriminatory processes. Although well established in the auditory domain, characteristics of the MMN are less well characterised in the visual domain. The five main studies presented in this thesis examine visual cortical processing using event-related potentials. Novel methodologies have been used to elicit visual detection and discrimination components in the absence of a behavioural task. Developing paradigms in which a behavioural task is not required may have important clinical applications for populations, such as young children, who cannot comply with the demands of an active task. The ‘pre-attentive’ nature of visual MMN has been investigated by modulating attention. Generators and hemispheric lateralisation of visual MMN have been investigated by using pertinent clinical groups. A three stimulus visual oddball paradigm was used to explore the elicitation of visual discrimination components to a change in the orientation of stimuli in the absence of a behavioural task. Monochrome stimuli based on pacman figures were employed that differed from each other only in terms of the orientation of their elements. One such stimulus formed an illusory figure in order to capture the participant’s attention, either in place of, or alongside, a behavioural task. The elicitation of a P3a to the illusory figure but not to the standard or deviant stimuli provided evidence that the illusory figure captured attention. A visual MMN response was recorded in a paradigm with no task demands. When a behavioural task was incorporated into the paradigm, a P3b component was elicited consistent with the allocation of attentional resources to the task. However, visual discrimination components were attenuated revealing that the illusory figure was unable to command all attentional resources from the standard deviant transition. The results are the first to suggest that the visual MMN is modulated by attention. Using the same three stimulus oddball paradigm, generators of visual MMN were investigated by recording potentials directly from the cortex of an adolescent undergoing pre-surgical evaluation for resection of a right anterior parietal lesion. To date no other study has explicitly recorded activity related to the visual MMN intracranially using an oddball paradigm in the absence of a behavioural task. Results indicated that visual N1 and visual MMN could be temporally and spatially separated, with visual MMN being recorded more anteriorly than N1. The characteristic abnormality in retinal projections in albinism afforded the opportunity to investigate each hemisphere in relative isolation and was used, for the first time, as a model to investigate lateralisation of visual MMN and illusory contour processing. Using the three stimulus oddball paradigm, no visual MMN was elicited in this group, and so no conclusions regarding the lateralisation of visual MMN could be made. Results suggested that both hemispheres were equally capable of processing an illusory figure. As a method of presenting visual test stimuli without conscious perception, a continuous visual stream paradigm was developed that used a briefly presented checkerboard stimulus combined with masking for exploring stimulus detection below and above subjective levels of perception. A correlate of very early cortical processing at a latency of 60-80 ms (CI) was elicited whether stimuli were reported as seen or unseen. Differences in visual processing were only evident at a latency of 90 ms (CII) implying that this component may represent a correlate of visual consciousness/awareness. Finally, an oddball sequence was introduced into the visual stream masking paradigm to investigate whether visual MMN responses could be recorded without conscious perception. The stimuli comprised of black and white checkerboard elements differing only in terms of their orientation to form an x or a +. Visual MMN was not recorded when participants were unable to report seeing the stimulus. Results therefore suggest that behavioural identification of the stimuli was required for the elicitation of visual MMN and that visual MMN may require some attentional resources. On the basis of these studies it is concluded that visual MMN is not entirely independent of attention. Further, the combination of clinical and non-clinical investigations provides a unique opportunity to study the characterisation and localisation of putative mechanisms related to conscious and non-conscious visual processing.

Reduced-Reference Image Quality Assessment Based on Edge Preservation

Assessing the subjective quality of processed images through an objective quality metric is a key issue in multimedia processing and transmission. In some scenarios, it is also important to evaluate the quality of the received images with minimal reference to the transmitted ones. For instance, for closed-loop optimisation of image and video transmission, the quality measure can be evaluated at the receiver and provided as feedback information to the system controller. The original images - prior to compression and transmission - are not usually available at the receiver side, and it is important to rely at the receiver side on an objective quality metric that does not need reference or needs minimal reference to the original images. The observation that the human eye is very sensitive to edge and contour information of an image underpins the proposal of our reduced reference (RR) quality metric, which compares edge information between the distorted and the original image. Results highlight that the metric correlates well with subjective observations, also in comparison with commonly used full-reference metrics and with a state-of-the-art reduced reference metric. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.

Special Section Guest Editorial: Image/Video Quality and System Performance

Rapid developments in display technologies, digital printing, imaging sensors, image processing and image transmission are providing new possibilities for creating and conveying visual content. In an age in which images and video are ubiquitous and where mobile, satellite, and three-dimensional (3-D) imaging have become ordinary experiences, quantification of the performance of modern imaging systems requires appropriate approaches. At the end of the imaging chain, a human observer must decide whether images and video are of a satisfactory visual quality. Hence the measurement and modeling of perceived image quality is of crucial importance, not only in visual arts and commercial applications but also in scientific and entertainment environments. Advances in our understanding of the human visual system offer new possibilities for creating visually superior imaging systems and promise more accurate modeling of image quality. As a result, there is a profusion of new research on imaging performance and perceived quality.