Digital Face Images Research Articles

A simple instrument designed to provide consistent digital facial images in dermatology

Photography has proven to be a valuable tool in the field of dermatology. The major reason for poor photographs is the inability to produce comparable images in the subsequent follow ups. Combining digital photography with image processing software analysis brings consistency in tracking serial images. Digital photographs were taken with the aid of an instrument which we designed in our workshop to ensure that photographs were taken with identical patient positioning, camera angles and distance. It is of paramount importance in aesthetic dermatology to appreciate even subtle changes after each treatment session which can be achieved by taking consistent digital images.

Memetically Optimized MCWLD for Matching Sketches With Digital Face Images

One of the important cues in solving crimes and apprehending criminals is matching sketches with digital face images. This paper presents an automated algorithm to extract discriminating information from local regions of both sketches and digital face images. Structural information along with minute details present in local facial regions are encoded using multiscale circular Weber's local descriptor. Further, an evolutionary memetic optimization algorithm is proposed to assign optimal weight to every local facial region to boost the identification performance. Since forensic sketches or digital face images can be of poor quality, a preprocessing technique is used to enhance the quality of images and improve the identification performance. Comprehensive experimental evaluation on different sketch databases show that the proposed algorithm yields better identification performance compared to existing face recognition algorithms and two commercial face recognition systems.

Performance Analysis for Detection and Location of Human Faces in Digital Image With Different Color Spaces for Different Image Formats

A human eye can detect a face in an image whether it is in a digital image or also in some video. The same thing is highly challenging for a machine. There are lots of algorithms available to detect human face. In this paper, a technique has been made to detect and locate the position of human faces in digital images. This approach has two steps. First, training the artificial neural network using Levenberg-Marquardt training algorithm and then the proposed algorithm has been used to detect and locate the position of the human faces from digital image. The proposed algorithm has been implemented for six color spaces which are RGB, YES, YUV, YCbCr, YIQ and CMY for each of the image formats bmp, jpeg, gif, tiff and png. For each color space training has been made for the image formats bmp, jpeg, gif, tiff and png. Finally, one color space and particular image format has been selected for face detection and location in digital image based on the performance and accuracy.

Non-photorealistic neural sketching

Abstract We present and evaluate a neural network-based technique to automatically enable NPR renderings from digital face images, which resemble semi-detailed sketches. The technique has been experimentally evaluated and compared with traditional approaches to edge detection (Canny and Difference of Gaussians, or DoG) and with a more recent variant, specifically designed for stylization purposes (Flow Difference of Gaussians, or FDoG). An objective evaluation showed, after an ANOVA analysis and a Tukey t-test, that the proposed approach was equivalent to the FDoG technique and superior to the DoG. A subjective experiment involving the opinion of human observers proved to be complementary to the objective analysis.

Threshold Based Human Face Detection

Face detection is the process of making a computer to determine the location of human faces in digital images. Face detection is considered as the essential first step in face recognition systems with the purpose of localizing and extracting the face region from the background. This paper implements a threshold based method to detect human faces from color images. The accuracy of our algorithm for face detection has been evaluated with images of complex background which varies in intensity and lighting conditions. The input image in the proposed system was tested using MATLAB with large set of input images.

Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics

Computer vision systems have demonstrated considerable improvement in recognizing and verifying faces in digital images. Still, recognizing faces appearing in unconstrained, natural conditions remains a challenging task. In this paper, we present a face-image, pair-matching approach primarily developed and tested on the "Labeled Faces in the Wild" (LFW) benchmark that reflects the challenges of face recognition from unconstrained images. The approach we propose makes the following contributions. 1) We present a family of novel face-image descriptors designed to capture statistics of local patch similarities. 2) We demonstrate how unlabeled background samples may be used to better evaluate image similarities. To this end, we describe a number of novel, effective similarity measures. 3) We show how labeled background samples, when available, may further improve classification performance, by employing a unique pair-matching pipeline. We present state-of-the-art results on the LFW pair-matching benchmarks. In addition, we show our system to be well suited for multilabel face classification (recognition) problem, on both the LFW images and on images from the laboratory controlled multi-PIE database.

Association of facial skin aging and vitamin D levels in middle-aged white women

To investigate the relationship between UV-induced skin photodamage and 25(OH) vitamin D levels, we performed a cross-sectional study in 45 female subjects aged >40. Menopausal status, smoking status, skin cancer history, oral supplement use, and season of blood draw were recorded and serum 25(OH)D measured. A single-blinded, dermatologist evaluated standardized digital facial images for overall photodamage, erythema/telangiectasias, hyperpigmentation, number of lentigines, and wrinkling. Adjusting for age and season of blood collection, women with lower photodamage scores were associated with a 5-fold increased odds of being vitamin D insufficient (OR 5.0, 95% CI: 1.1, 23). Low scores for specific photodamage parameters including erythema/telangiectasias, hyperpigmentation, and wrinkling were also significantly associated with vitamin D insufficiency. Our results suggest an association between skin aging and 25(OH)D levels.

Selective attention toward female secondary sexual color in male rhesus macaques

Pink-to-red anogenital and facial sexual skin occurs in females of many primate species. Since female sexual skin color varies with reproductive state, it has long been assumed that color acts to stimulate male sexual interest. Although there is supportive evidence for this as regards anogenital skin, it is unclear whether this is also the case for facial sexual skin. In this study we experimentally manipulated digital facial and hindquarter images of female rhesus macaques (Macaca mulatta) for color within the natural range of variation. The images were presented to adult male conspecifics to assess whether the males exhibited visual preferences for red vs. non-red female coloration, and whether preferences varied with anatomical region. The males displayed significantly longer gaze durations in response to reddened versions of female hindquarters, but not to reddened versions of faces. This suggests that female facial coloration may serve an alternative purpose to that of attracting males, and that the signal function of sexual skin and the intended recipients may vary across anatomical regions.

Influence of lip support on the soft‐tissue profile of complete denture wearers

Complete dentures change the soft-tissue profile, although the exact relationship remains unclear. This study examined the relationship between the presence and degree of lip support provided by dentures and the lateral views of the facial appearance of edentulous patients. The subjects were five edentulous patients (three men and two women). Their facial appearances with experimental record blocks, with and without their complete dentures, were measured using a three-dimensional laser measuring system. The experimental record block for each subject had different conditions in the anteroposterior direction anteriorly but the same vertical dimensions posteriorly. The lateral digital facial images were displayed on a computer monitor, and the linear and angular measurements were analysed using image analysis software. The nasolabial angle was smaller and the labial points projected more with excessive lip support versus with deficient support. Moreover, the counter of the nose was affected by the labial flange of the record base, particularly in the facial appearance of one subject with highly atrophic residual ridges. The lip support affected the lower facial soft-tissue profile, including the lower part of the nose; the nasolabial angle and positional relationship between the lips and Ricketts's esthetic plane (E plane) are useful indexes for examining lip support.

Eigenspace-Based Face Recognition: A Comparative Study of Different Approaches

Eigenspace-based face recognition corresponds to one of the most successful methodologies for the computational recognition of faces in digital images. Starting with the Eigenface-Algorithm, different eigenspace-based approaches for the recognition of faces have been proposed. They differ mostly in the kind of projection method used (standard, differential, or kernel eigenspace), in the projection algorithm employed, in the use of simple or differential images before/after projection, and in the similarity matching criterion or classification method employed. The aim of this paper is to present an independent comparative study among some of the main eigenspace-based approaches. We believe that carrying out independent studies is relevant, since comparisons are normally performed using the implementations of the research groups that have proposed each method, which does not consider completely equal working conditions for the algorithms. Very often, a contest between the abilities of the research groups rather than a comparison between methods is performed. This study considers theoretical aspects as well as simulations performed using the Yale Face Database, a database with few classes and several images per class, and FERET, a database with many classes and few images per class.

When facial attractiveness is only skin deep.

Whilst the relationship between aspects of facial shape and attractiveness has been extensively studied, few studies have investigated which characteristics of the surface of faces positively influence attractiveness judgments. As many researchers have proposed a link between attractiveness and traits that appear healthy, apparent health of facial skin might be a property of the surface of faces that positively influences attractiveness judgments. In experiment 1 we tested for a positive correlation between ratings of the apparent health of small skin patches (extracted from the left and right cheeks of digital face images) and ratings of the attractiveness of male faces. By using computer-graphics faces, in experiment 2 we aimed to establish if apparent health of skin influences male facial attractiveness independently of shape information. Results suggest that apparent health of facial skin is correlated both with ratings of male facial attractiveness (experiment 1) and with being a visual cue for judgments of the attractiveness of male faces (experiment 2). These findings underline the importance of controlling for the influence of visible skin condition in studies of facial attractiveness and are consistent with the proposal that attractive physical traits are those that positively influence others' perceptions of an individual's health.

Automatic forensic face recognition from digital images.

Digital image evidence is now widely available from criminal investigations and surveillance operations, often captured by security and surveillance CCTV. This has resulted in a growing demand from law enforcement agencies for automatic person-recognition based on image data. In forensic science, a fundamental requirement for such automatic face recognition is to evaluate the weight that can justifiably be attached to this recognition evidence in a scientific framework. This paper describes a pilot study carried out by the Forensic Science Service (UK) which explores the use of digital facial images in forensic investigation. For the purpose of the experiment a specific software package was chosen (Image Metrics Optasia). The paper does not describe the techniques used by the software to reach its decision of probabilistic matches to facial images, but accepts the output of the software as though it were a 'black box'. In this way, the paper lays a foundation for how face recognition systems can be compared in a forensic framework. The aim of the paper is to explore how reliably and under what conditions digital facial images can be presented in evidence.

An Efficient Feature Extraction Method with Pseudo-Zernike Moment in RBF Neural Network-Based Human Face Recognition System

This paper introduces a novel method for the recognition of human faces in digital images using a new feature extraction method that combines the global and local information in frontal view of facial images. Radial basis function (RBF) neural network with a hybrid learning algorithm (HLA) has been used as a classifier. The proposed feature extraction method includes human face localization derived from the shape information. An efficient distance measure as facial candidate threshold (FCT) is defined to distinguish between face and nonface images. Pseudo-Zernike moment invariant (PZMI) with an efficient method for selecting moment order has been used. A newly defined parameter named axis correction ratio (ACR) of images for disregarding irrelevant information of face images is introduced. In this paper, the effect of these parameters in disregarding irrelevant information in recognition rate improvement is studied. Also we evaluate the effect of orders of PZMI in recognition rate of the proposed technique as well as RBF neural network learning speed. Simulation results on the face database of Olivetti Research Laboratory (ORL) indicate that the proposed method for human face recognition yielded a recognition rate of 99.3%.

デジタルカメラを用いた顔貌分析の試み システムならびに義歯装着者への応用の検討

In this study, a new analyzing system was developed to evaluate the facial appearance of denture wearers affected by inadequate dentures and aging. In this system, the frontal and lateral digital facial images captured using a digital camera were displayed on a computer monitor and were analyzed according to the linear and angular measurements by image analysis software.This system required a short time to complete the analysis, and showed high reliability because the dimensional error on image distortion and difference of lens-subject distance was small. The facial images of 59 dentulous subjects (44 males and 15 females aged 23 to 29 years) were analyzed. Furthermore, this system and a polygon (a standard deviation diagram) from the data on the male dentulous subjects were applied to the analysis of the facial appearance of a denture wearer (78-year-old male).Dentures were useful to obtain lip support, but the effect of denture wearing was different for the analytical items. It was speculated that the differences in measurements between the edentulous subject with dentures and dentulous subjects were caused by aging and/or features of each edentulous subject.This system could be useful for routine clinical use in prosthetic dentistry.

Off-the-shelf digital imaging/prediction

The current digital camera we use is the Olympus D320 L (Olympus America, Inc., Melville, N.Y.); it features macro capabilities, auto focus and flash, color LCD screen, TWAIN driver for serial port download, 1024 x 768 resolution, and free Adobe PhotoDeluxe software (Adobe Software, San Jose, Calif.) that is included in the package. (Editor's NOTE 1.) For routine grouping, cropping, printing, compression, storage, and retrieval from hard disk, we use DentoFacial Showcase software (DentoFacial Software, Toronto, Canada). PhotoDeluxe is a simplified version of the professional Adobe PhotoShop imaging software used in many professional film studios. In complex cases involving anticipated facial changes, treatment projections are helpful aids in communication to patient and surgeon. We have found Adobe PhotoDeluxe to be very useful in this process. This technique of image manipulation is not grounded in scientific research or statistics but is an interpolation of manual cephalometric prediction and the facial image. The cephalometric prediction tracing techniques have been described by many authors and are well documented; I find Epker and Fish's 1 text, Dental Deformities, Integrated Orthodontics, and Surgical Correction, to be very helpful. As an example, an adult Class II Division 1 patient with retrognathic profile may not understand the concept of extraction of four first premolars versus extraction of lower premolars with mandibular advancement osteotomy as it relates to facial appearance. Demonstrating the cephalometric tracing prediction and before and after photographs of similar patients may be confusing to the patient. In the past, we would take the patient's pretreatment photographs, cut them with scissors, and reassemble the pieces to represent posttreatment expectations. Now we manipulate the patient's pretreatment digital image (Fig. 1). The digital facial images are taken with two millimetric rulers in the field oriented in the x and y axis. (See editor's enhancements.) These should be close enough to the subject that they remain visible after cropping. It also helps to have an absolutely white background; we use a slave bounce flash to accomplish this. The cephalometric tracing is worked up with dental, bony, and soft tissue posttreatment predictions. Overlaying the original tracing will reveal the two-dimensional changes of the soft tissue chin and lip profile relative to the x and y planes. It is then a simple matter of transferring these alterations to the image. The image can be downloaded from the camera directly to PhotoDeluxe or imported from the hard disk file. In the case of our adult Class II patient for orthognathic treatment, pogonion is moved anteriorly and inferiorly. To do this, trace the mandible with the cursor and use the editing tools to copy and cut the area and paste it in its new position based on the prediction tracing held up to the monitor screen. (Editor's NOTE 2.) The superimposed rulers help if the image cannot be zoomed to fit the tracing precisely. There is no need to worry about edges not lining up at the cut marks or shading discrepancies at this time. Similar alterations are then made to the soft tissue profile according to interpretation from the cephalometric prediction. After gross movements are accomplished, the areas of rough edges, overlapping, and shading are smoothed out with the paint, erase, and smudge tools. The rulers can be erased in the same manner. These refinements can be accomplished over large areas or even one pixel at a time with the zoom-in feature. The changed image is saved, and the original is edited again with prediction tracings used for the nonsurgical treatment option. In this Class II case, little change in pogonion is registered, but maxillary soft tissue drape and upper and lower lip are altered to a retroposition to simulate retraction to Class I. Refinement editing is done as before. The new images can now be printed, incorporated in correspondence, or exported back to Showcase for storage in the patient's image file. Several very sophisticated orthodontic/orthognathic prediction programs are on the market; these are excellent and require less input time. The above procedure is only as accurate as the