METAMERISM INDEX OF LED LIGHT ON HALFTONE COLOUR IMAGES

Skin face detection in photo imaging, is an important component of systems for detecting similarities in visual perception, tracing faces through illumination and metamerism. This paper presents an evaluation of the skin perception under standardized conditions of varied light sources: cool-white fluorescent “store light”, 6500K fluorescent “daylight”, and incandescent “home light”, Led light 6500 K, 2700K, 4000K CCT. In cases where the discrepancy is large, the resulting index of metamerism can be misleading. A small index of metamerism and a large change of color under illuminant metamerism has a different interpretation than what is perceived. This has been demonstrated through small colour variations in print through CMYK colors. The implication is that particular indices of metameric should only account for a limited range under different light conditions. The method used in this paper is based on visual perception, which aim to work with a wide variety of individuals, under varying lighting conditions under the influence of standard daylight, but in this case we also used the Led light 6500K correlated colour temperature, and variations of skin color tones, comparing the illuminant metamerism of visual perception based on different reflectance power distributions (SPDs)

Statistical colour models: an automated digital image analysis method for quantification of histological biomarkers

Background: Colour is the most important feature used in quantitative immunohisto- chemistry (IHC) image analysis; IHC is used to provide information relating to aetiology and to con rm malignancy. Methods: Statistical modelling is a technique widely used for colour detection in computer vision. We have developed a statistical model of colour detection applicable to detection of stain colour in digital IHC images. Model was rst trained by massive colour pixels collected semi-automatically. To speed up the training and detection processes, we removed luminance channel, Y channel of YCbCr colour space and chose 128 histogram bins which is the optimal number. A maximum likelihood classi- er is used to classify pixels in digital slides into positively or negatively stained pixels automatically. The model-based tool was developed within ImageJ to quantify targets identi ed using IHC and histochemistry. Results: The purpose of evaluation was to compare the computer model with human evaluation. Several large datasets were prepared and obtained from human oesopha- geal cancer, colon cancer and liver cirrhosis with di erent colour stains. Experimental results have demonstrated the model-based tool achieves more accurate results than colour deconvolution and CMYK model in the detection of brown colour, and is comparable to colour deconvolution in the detection of pink colour. We have also demostrated the proposed model has little inter-dataset variations. Conclusions: A robust and e ective statistical model is introduced in this paper. The model-based interactive tool in ImageJ, which can create a visual representation of the statistical model and detect a speci ed colour automatically, is easy to use and avail- able freely at http://rsb.info.nih.gov/ij/plugins/ihc-toolbox/index.html. Testing to the tool by di erent users showed only minor inter-observer variations in results

Performance analysis of ANN based YCbCr skin detection algorithm

Skin detection from acquired images has various areas of applications especially in automatic facial and human recognition system. The performance analysis of artificial neural network based –YcbCr skin recognition and three other techniques is evaluated in this work. Results obtained show that the use of YCbCr color model performs better than RGB colour model and the use of artificial neural network further improves the accuracy of the system

An investigation into the efficacy of single low dose of insulin in the prevention of excessive cutaneous scarring in breast surgery

Early human fetuses have the ability to heal wounds by completely regenerating tissues, leaving no evidence of scarring. However in the adult scarring is the inevitable endpoint of the wound healing process. Sometimes these scars can be pathological in nature causing both functional and aesthetic problems to those affected. Every year millions of people around the globe acquire problematic or pathological scars either whilst undergoing surgery or from traumatic injuries and at present there remain a severely limited number of pharmacological treatment options to offer these patients. Importantly currently there exists no treatment that can either eliminate or reliably reduce acquired scars. Not only is the treatment of acquired scars problematic but also the clinical assessment of scars is largely subjective in nature and frequently relies on assessment scales that show large amounts of inter-rater variation and lack quantification. Especially subjective is the measurement of scar colour, which can be markedly different from the surrounding skin and cause significant distress to the patient. Without an objective assessment framework clinicians cannot reliably examine scars nor gauge responses to any treatment. The aim of this thesis is thus two-fold. Firstly a new anti-scarring treatment in the form of insulin will be tested in a randomised, double blind, intra-patient, placebo controlled trial where patients undergoing elective bilateral breast surgery will have low-dose insulin injected subcutaneously to one breast and placebo to the other at the time of surgery. Patients will be followed up for 12 months and their scars compared to examine the therapeutic effect of insulin upon scars. Secondly the thesis aims to test the validity of new methods of assessing the scar colour of a subset of patients within the insulin trial using previously untested photographic devices and software. These devices are hoped to add much needed quantification to scar assessment.Open Acces

Particle Filters for Colour-Based Face Tracking Under Varying Illumination

Automatic human face tracking is the basis of robotic and active vision systems used for facial feature analysis, automatic surveillance, video conferencing, intelligent transportation, human-computer interaction and many other applications. Superior human face tracking will allow future safety surveillance systems which monitor drowsy drivers, or patients and elderly people at the risk of seizure or sudden falls and will perform with lower risk of failure in unexpected situations. This area has actively been researched in the current literature in an attempt to make automatic face trackers more stable in challenging real-world environments. To detect faces in video sequences, features like colour, texture, intensity, shape or motion is used. Among these feature colour has been the most popular, because of its insensitivity to orientation and size changes and fast process-ability. The challenge of colour-based face trackers, however, has been dealing with the instability of trackers in case of colour changes due to the drastic variation in environmental illumination. Probabilistic tracking and the employment of particle filters as powerful Bayesian stochastic estimators, on the other hand, is increasing in the visual tracking field thanks to their ability to handle multi-modal distributions in cluttered scenes. Traditional particle filters utilize transition prior as importance sampling function, but this can result in poor posterior sampling. The objective of this research is to investigate and propose stable face tracker capable of dealing with challenges like rapid and random motion of head, scale changes when people are moving closer or further from the camera, motion of multiple people with close skin tones in the vicinity of the model person, presence of clutter and occlusion of face. The main focus has been on investigating an efficient method to address the sensitivity of the colour-based trackers in case of gradual or drastic illumination variations. The particle filter is used to overcome the instability of face trackers due to nonlinear and random head motions. To increase the traditional particle filter\u27s sampling efficiency an improved version of the particle filter is introduced that considers the latest measurements. This improved particle filter employs a new colour-based bottom-up approach that leads particles to generate an effective proposal distribution. The colour-based bottom-up approach is a classification technique for fast skin colour segmentation. This method is independent to distribution shape and does not require excessive memory storage or exhaustive prior training. Finally, to address the adaptability of the colour-based face tracker to illumination changes, an original likelihood model is proposed based of spatial rank information that considers both the illumination invariant colour ordering of a face\u27s pixels in an image or video frame and the spatial interaction between them. The original contribution of this work lies in the unique mixture of existing and proposed components to improve colour-base recognition and tracking of faces in complex scenes, especially where drastic illumination changes occur. Experimental results of the final version of the proposed face tracker, which combines the methods developed, are provided in the last chapter of this manuscript

An Analysis of the art image interchange cycle within fine art museums

The art image interchange cycle is the procedure carried out by fine art museums in reproducing fine artwork --starting with the imaging of the original work, then digital processing, and lastly, repurposing for output to achieve a high-quality replica in a range of possible media. There are many areas of importance within this process, such as digital image processing, standardization, test targets use, and color management. This research has sought to analyze the fine art image interchange through understanding the background areas and how they apply, as well as benchmarking what museums are already doing with the intention of improving and standardizing the process. Upon completion of an adequate background study of the literature (concentrated on color management theory, test targets use, and fine art reproduction) this research focused on four main areas. First, a review of international standards was established and how they can be used to benefit museums. Second, a review of test targets was conducted and how best they can be implemented in fine art reproduction. Third, a number of museum workflows were benchmarked and documented - a workflow experiment was created and implemented for documentation purposes (and future image quality analysis). Lastly, a case study was conducted of a local fine art museum\u27s process of creating a fine art catalog, to better understand an average museum\u27s fine art image interchange. The research concluded that the practice of standardization could be improved within museums. As far as test targets, there was a large range of understanding and use. The benchmarking of three museums was completed, and it was determined that the process of documenting workflow was a difficult task to have implemented. Lastly, in x the case study, much was gained through the interviews, placing a great importance on communication, planning, and standardization

Accurate Colour Reproduction of Human Face using 3D Printing Technology

The colour of the face is one of the most significant factors in appearance and perception of an individual. With the rapid development of colour 3D printing technology and 3D imaging acquisition techniques, it is possible to achieve skin colour reproduction with the application of colour management. However, due to the complicated skin structure with uneven and non-uniform surface, it is challenging to obtain accurate skin colour appearance and reproduce it faithfully using 3D colour printers. The aim of this study was to improve the colour reproduction accuracy of the human face using 3D printing technology. A workflow of 3D colour image reproduction was developed, including 3D colour image acquisition, 3D model manipulation, colour management, colour 3D printing, postprocessing and colour reproduction evaluation. Most importantly, the colour characterisation methods for the 3D imaging system and the colour 3D printer were comprehensively investigated for achieving higher accuracy

Color in computing

Color in the computing environment, once considered a luxury, is becoming more available compared to being just the occasional exception. As the number of users exploring the uses of color through displayed and printed images increases, the problems associated with its use are becoming widely known. What worked in black and white is not easily translated into color. The use of color needs to begin with the basic understanding of what is color, its terminology and its utilization as an enhancement to communications tool. Only after the basic terminology and effective means of communication are understood will color flourish as a successful means of communication in the computing environment. Currently, a number of products are seen as solutions in the realm of color usage in the computing environment. Four different contributions, PostScript Level 2 (Adobe), PhotoYCC(Eastman Kodak), Pantone Matching System (Pantone), and TekHVC (Tektronix), each deliver a component of electronic color reproduction. PostScript Level 2 delivers consistent color from monitor to printer, with variations based on printer manufacture and the printing technology utilized. PhotoYCC defines a format for image capture and retrieval with a wealth of possibilities for image sources. Pantone Matching System expands the accessibility of simulated prepress work, coupled with ink formulation and quality control. Tektronix attempted to define TekHVC as an industry standard based on a more uniform color space than that which is defined by previous industry standards. Because of the lack of acceptance, Tektronix has limited this solution to their printers. Solutions are abundant, but as costs continue to fall, the expectation of consistent color will rise. The adoption of standards across operating environments and software packages is critical to continued increase of the use of color in the computing environment

Immunohistochemistry image analysis : protein, nuclei and gland

This thesis focus on the analysis of digitized microscopic image, especially on IHC stained colour images. The corresponding contributions focused on the automatic detection of stain colour and glands, the segmentation and quantification of cell nuclei, the analysis of liver cirrhosis and the development of a semi-automatic toolbox. Colour is the most important feature in the analysis of immunostained images. We developed a statistical colour detection model for stain colour detection based on the histograms of collected colour pixels. This is acting on the approach "what you see is what you get" which outperforms the other methods on the detection of several kinds of stain colour. Verifying the presence of nuclei and quantifying positive nuclei is the foundation of cancer grading. We developed a novel seeded nuclei segmentation method which greatly improves the segmentation accuracy and reduces both over-segmentation and under-segmentation. This method has been demonstrated to be robust and accurate in both segmentation and quantification against manual labelling and counting in the evaluation process. The analysis of gland architecture, which reflects the cancer stage, has evolved into an important aspect of cancer detection. A novel morphology-based approach has been developed to segment gland structures in H-DAB stained images. This method locates the gland by focusing on its morphology and intensity characteristics, which covers variations in stain colours in different IHC images. The evaluation results have demonstrated the improvements of accuracy and efficiency. For the successive development of three methods, we put them in a semi-automatic toolbox for the aid of IHC image analysis. It can detect different kinds of stain colour and the basic components in an IHC image. The user created models and parameters can be saved and transferred to different users for the reproduction of detection results in different laboratories. To demonstrate the flexibility of our developed stained colour detection technique, the tool has been extended to the analysis of liver cirrhosis. It is a novel method based on our statistical colour detection model which greatly improves the analysis accuracy and reduces the time cost