Image Subtraction Technique Research Articles

Volumetric Changes of the Mid and Lower Face with Animation and the Standardization of Three-Dimensional Facial Imaging.

The objective of this study was to quantify volumetric changes of the mid and lower face caused by facial expression to understand how procedural results measured by three-dimensional imaging can be influenced by lack of standardization. Secondarily, the study identified soft-tissue surface landmarks that can be used to ensure the standardization of three-dimensional images. Three-dimensional facial images of subjects performing 22 facial expressions or changes in head position were captured. Variable degrees of animation during smiling and frowning were also evaluated. Volumetric changes of the malar and jowl regions were quantified using a three-dimensional superimposed image subtraction technique. The translation of 14 standard soft-tissue surface landmarks was assessed during various facial animations to determine which three-dimensional landmarks can be used to standardize three-dimensional images. Twenty subjects participated in the study. Sixteen of the 22 facial expression studies had a significant effect on malar and/or jowl volume. Significant volume changes were noted with subtle animation during smiling and frowning. A combination of five landmarks (i.e., glabella, bilateral cheilion, pogonion, and laryngeal prominence) can be used to standardize three-dimensional images for evaluation of mid and lower facial volume changes. Subtle facial expressions may cause significant volumetric changes in the mid and lower face that can mimic the desired outcomes of surgical and nonsurgical facial rejuvenation procedures. The five-point referencing system allows one to identify subtle changes in head position and facial expression and may aid in the standardization of three-dimensional images.

Visual study of explosive particles during fast thermal analysis

A study of visual changes occurred during fast thermal analysis of explosive and non-explosive micrometric particles is presented. The experimental setup is based on a microcalorimeter MEMS device which allows linear temperature rising at high heating rates. The micro thermal analysis at high heating rates of ∼500 °C/s was performed on tens of micrometer size particles while observing and filming the process using a digital camera (Sensicam™) operated at a rate of 45 frames per second. The study also employs image subtraction technique which emphasizes the changes occurred between following images. The measurements and image processing reveal that: 1) the observed visual changes are in accordance with the thermal response; 2) thermogram events are well explained by visual observation, thus the last contributes more dimensions to the measurement.

Abstract: Volumetric Changes of the Mid and Lower Face with Animation and the Standardization of 3D Facial Imaging

GOALS: 3D photography provides volumetric data and surface topography with sub-millimeter precision, but current methods lack standardization for facial expression and position. For example, smiling can mimic the desired outcomes of a facelift and fat grafting by increasing malar volume while decreasing volume in the jowls. Our goal was to quantify volumetric changes of the mid and lower face caused by facial expression so that we can accurately assess volumetric changes after surgery. Secondarily, we aimed to identify soft tissue landmarks that can be used to detect these changes in facial expression or head position to ensure the standardization of 3D images. METHODS: 3D facial images of 16 subjects performing 22 facial expressions or changes in head position were captured. Variable degrees of animation during smiling and frowning were also evaluated. Volumetric changes of the malar and jowl regions with facial expressions were quantified using a 3D superimposed image subtraction technique. Translation (movement >1 mm) of 14 standard soft tissue surface landmarks was assessed during various facial animations to determine which landmarks can be utilized to standardize 3D images. RESULTS: Sixteen of the 22 facial expression studied had a significant effect on malar and/or jowl volume. Significant volume changes were noted with subtle animation during smiling and frowning. During maximal smile, mean excursion of oral commissures was 13.7mm +/- 3.0 and the malar region demonstrated a 17.2mL +/- 5.7 increase in volume, whereas the jowl region demonstrated a 1.7mL+/- 0.9 decrease in volume. During maximal frowning, mean excursion of oral commissures was 7.4mm +/- 2.3. The malar region demonstrated a 3.7mL +/- 2.3 decrease in volume, whereas the jowl region demonstrated a 5.4mL +/- 0.9 increase in volume. In the act of smiling, there was significant volume augmentation of the malar region with small degrees of oral commissure excursion, such that a quarter smile (excursion = 25% of excursion with maximal smile) could induce a volume change equivalent to 75% of maximum smile. The jowl decreases in volume with smiling, but in a linear fashion (a quarter smile yields a volume change equivalent to 25% of a maximum smile). Frowning exhibited the opposite, but similarly significant changes in mid and lower facial volume. A 1mm commissure excursion during smiling can produce 5-10mL of malar augmentation or 2-4mL of jowl augmentation with frowning. We believe these results are related to isometric contraction of mimetic muscles and their influence on fat compartments. A combination of 5 landmarks (glabella, bilateral cheilion, pogonion and laryngeal prominence) was found to indicate all tested facial expressions which effect mid and facial volumes, with the exception of platysmal straining. CONCLUSION: Most facial expressions will lead to translation of the oral commissures, with even a subtle (1mm) excursion leading to 5-10mL of malar augmentation during smiling or 2-4mL of jowl augmentation during frowning. We identified that the glabella, pogonion, laryngeal prominence, and bilateral cheilion can be used as a referencing system to allow identification of subtle changes in head position and facial expression for standardization of 3D images.

DVC‐based image subtraction to detect microcracking in lightweight concrete

AbstractThis paper presents an image subtraction technique based on digital volume correlation to detect and extract the complex network of microcracks that progressively developed in a lightweight concrete sample submitted in situ to uniaxial compression and imaged by X‐ray computed tomography. From local digital volume correlation measurements, performed only on positions with sufficient image contrast, the mechanical transformation is estimated at all voxels within the whole sample using an adjusted interpolation procedure that computes an affine approximation of the local transformation. The deformed image (containing cracks) is thus transformed back to the same frame as the reference image (without cracks) to compute the difference between both images, taking into account possible brightness and contrast adjustments. The resulting subtracted image reveals the path of cracks, which is clearly visible without the underlying heterogeneous microstructure of the concrete. The detection accuracy is here estimated to one tenth of a voxel, allowing early‐age cracks to be detected while they would barely have been noticed on the X‐ray computed tomography images. Segmentation of the crack network is also made much easier. To overcome a low signal‐to‐noise ratio for the tiniest cracks, a Hessian‐based filter is used to extract the complex crack network. The cracks can be directly located in the microstructure segmented in the reference image and compared for all loading steps to characterise their initiation and propagation.

The zenithal 4-m International Liquid Mirror Telescope: a unique facility for supernova studies

The 4-m International Liquid Mirror Telescope (ILMT) will soon become operational at the newly developed Devasthal observatory near Nainital (Uttarakhand, India). Coupled with a 4k $\times$ 4k pixels CCD detector and TDI optical corrector, it will reach approximately 22.8, 22.3 and 21.4 magnitude in the $g'$, $r'$ and $i'$ spectral bands, respectively in a single scan. The limiting magnitudes can be further improved by co-adding the consecutive night images in particular filters. The uniqueness to observe the same sky region by looking towards the zenith direction every night, makes the ILMT a unique instrument to detect new supernovae (SNe) by applying the image subtraction technique. High cadence ($\sim$24 hours) observations will help to construct dense sampling multi-band SNe light curves. We discuss the importance of the ILMT facility in the context of SNe studies. Considering the various plausible cosmological parameters and observational constraints, we perform detailed calculations of the expected SNe rate that can be detected with the ILMT in different spectral bands.

Identifying Rings in IFU Surveys

Gravitational lensings provide unique opportunities to study distant galaxies. Despite their usefulness, only a dozens of gravitational arcs have been reported up-to-date, hampered by the low resolution imaging from ground-based surveys. We propose a novel method to identify Einstein rings/arcs in the IFU surveys via image subtraction and computer vision techniques. We use the recent discovered strong lens system in the MaNGA survey as a proof-of-concept; in addition to MaNGA, our approach is applicable to other IFU surveys, such as SAMI, CALIFA, Hector, DESI, and 4MOST.

Optic Disc Image Subtraction as an Aid to Detect Glaucoma Progression.

PurposeTo present a digital image subtraction technique to alert clinicians to signs of glaucomatous optic disc progression.MethodsNinety-two glaucomatous eyes (65 patients) were included. Thirty-three eyes were identified as progressive and 59 as stable based on comparison of baseline and follow-up stereoscopic disc photographs by three masked glaucoma specialists. The disc images were aligned and converted to gray scale and underwent histogram matching to enhance contrast and account for illumination differences. The difference in image intensity between baseline and follow-up images was shown as a colormap superimposed on the grayscale follow-up image. A graded scale (1, no progression, to 5, definitive progression) was used by three masked glaucoma experts to score progression probability on the colormap images. Sensitivity, specificity, and accuracy of the classification were computed. Weighted κ statistics summarized agreement of categorical gradings.ResultsMedian time interval between two visits was 4.4 years (range: 1.0–16.8). Clinicians detected glaucoma deterioration in 25 to 27 of the progressive group and 8 to 10 of stable eyes based on subtraction maps. Sensitivities/specificities of the clinicians were 0.76 to 0.82 and 0.86 to 0.89, respectively. Classification accuracy ranged from 81.5% to 84.8%. Agreement among clinicians was good (weighted κ = 0.68; 95% confidence interval [CI]: 0.60–0.77) for progression grades (1–5 scales) and was substantial (weighted κ = 0.81; 95% CI: 0.74–0.85) for binary scores.ConclusionsThe proposed software provides a single static image that clinicians can use with other structural/functional tests to detect glaucoma progression.Translational RelevanceProvision of a subtraction colormap in the setting of electronic medical records can improve monitoring of glaucoma by alerting clinicians to possible signs of progression.

Evaluation of the rockburst potential in longwall coal mining using passive seismic velocity tomography and image subtraction technique

Rockburst is a typical dynamic disaster in underground coal mines which its occurrences relate to the mechanical quality of coal seam and surrounding rock mass and also the condition of stress distribution. The main aim of this paper is to study the potential of rockburst in a longwall coal mine by using of passive seismic velocity tomography and image subtraction technique. For this purpose, first by mounting an array of receivers on the surface above the active panel, the mining-induced seismic data as a passive source for several continuous days were recorded. Then, the three-dimensional tomograms using simultaneous iteration reconstruction technique (SIRT) for each day are created and by employing the velocity filtering, the overstressed zones are detected. In addition, the two-dimensional seismic velocity tomograms in coal seam level by slicing the three-dimensional tomograms are obtained. Then the state of stress changes in successive days by applying the image subtraction technique on these two-dimensional tomograms is considered. The results show that the compilation of filtered three-dimensional tomograms and subtracted images is an appropriate approach for detecting the overstressed zones around the panel and subsequent evaluation of rockburst potential. The research conclusion proves that the applied approach in this study in combination with field observations of rock mass status can effectively identify the rockburst-prone areas during the mining operation and help to improve the safety condition.

AN AO-ASSISTED VARIABILITY STUDY OF FOUR GLOBULAR CLUSTERS*

ABSTRACT The image-subtraction technique applied to study variable stars in globular clusters represented a leap in the number of new detections, with the drawback that many of these new light curves could not be transformed to magnitudes due to severe crowding. In this paper, we present observations of four Galactic globular clusters, M 2 (NGC 7089), M 10 (NGC 6254), M 80 (NGC 6093), and NGC 1261, taken with the ground-layer adaptive optics module at the SOAR Telescope, SAM. We show that the higher image quality provided by SAM allows for the calibration of the light curves of the great majority of the variables near the cores of these clusters as well as the detection of new variables, even in clusters where image-subtraction searches were already conducted. We report the discovery of 15 new variables in M 2 (12 RR Lyrae stars and 3 SX Phe stars), 12 new variables in M 10 (11 SX Phe and 1 long-period variable), and 1 new W UMa-type variable in NGC 1261. No new detections are found in M 80, but previous uncertain detections are confirmed and the corresponding light curves are calibrated into magnitudes. Additionally, based on the number of detected variables and new Hubble Space Telescope/UVIS photometry, we revisit a previous suggestion that M 80 may be the globular cluster with the richest population of blue stragglers in our Galaxy.

Noise Reduction in Abdominal Computed Tomography Applying Iterative Reconstruction (ADMIRE)

The study aimed to compare image quality of filtered back projection (FBP) and iterative reconstruction (advanced modeled iterative reconstruction, ADMIRE) in contrast-enhanced computed tomography (CT) of the abdomen, and to assess the differences of reconstructions according to these methods. It also aimed to investigate the potential for noise reduction of ADMIRE for different reconstructed slice thicknesses. CT data of the abdomen and pelvis were acquired using a 128-slice single-source CT system using automated kV selection and tube current adaption based on patients' anatomy. Raw data sets from patients scanned at 100 kV were selected, and images were reconstructed with slice thicknesses of 1 mm, 3 mm, and 5 mm, both with FBP and ADMIRE. Filter strength F1, F3, and F5 of the ADMIRE algorithm and the corresponding reconstruction kernels were used. In total, 58 raw data sets from 17 patients were used to reconstruct from the same raw data FBP and ADMIRE images, representing identical body regions. Identical regions of interest were placed at the same position of up to four images and image noise was measured. Differences of reconstructed images and detail preservation were tested using an image subtraction technique, and subjective image quality was assessed using a 5-point Likert scale. On average, for 1-mm slice thickness, noise reduction was 9.15% ± 2.4% with filter strength level F1, 30.2% ± 3.4% with F3, and 54.4% ± 7.0% with F5 as compared to FBP. For a slice thickness of 3 mm, noise reduction was 8.5% ± 3.7% with F1, 28.6% ± 3.9% with F3, and 52.2% ± 9.1% with F5. For 5 mm, the corresponding values are 8.9% ± 2.7%, 31.4% ± 2.8%, and 52.7% ± 7.7%. On subtraction images, edge information of tissue classes with a high attenuation gradient was found, but structures with small differences in attenuation were not detectable on subtraction images, confirming that no relevant details were lost in the iterative reconstruction process. ADMIRE is able to reduce image noise considerably (up to 50%) without any obvious negative impact on lesion depiction as assessed visually. Noise reduction of ADMIRE seems to be independent of slice thickness.

COMPUTER VISION SYSTEM FOR AUTOMATIC CERAMIC TILES INSPECTION

Ponte Academic JournalSep 2016, Volume 72, Issue 9 COMPUTER VISION SYSTEM FOR AUTOMATIC CERAMIC TILES INSPECTIONAuthor(s): POLEPOGU RAJESH ,KUNDURU UMAMAHESWARIJ. Ponte - Sep 2016 - Volume 72 - Issue 9 doi: 10.21506/j.ponte.2016.9.16 Abstract:Quality control is an important issue in the ceramic tile industry. On the other hand maintaining the rate of production with respect to time is also a major issue in ceramic tile manufacturing. Due to massive production of ceramic tiles, using human resources for defect detection is quite tedious and time consuming process. So we need to automate the process. Various optical technology based approaches came into play such as Automatic Optical Imaging. It is effective but very expensive technique for small-scale manufacturers. Therefore, many researchers started developing image processing algorithms for defect detection in ceramic tiles using less expensive cameras. In this paper we proposed an automated computer vision system with efficient defect detection technique, which can detect surface defects like blobs and cracks on tiles with high accuracy and fast response. This automated method helps us to acquire knowledge about the pattern of defect within a very short span of time. To automate the whole process, we have developed a ‘Graphical User Interface’ (GUI) in MATLAB using GUIDE (Graphical user interface design environment). We have used Sobel operator for edge detection and image subtraction techniques for fault detection in ceramic tiles. Index Terms— CV (Computer Vision), GUI (Graphical User Interface), GUIDE (Graphical user interface design environment), Threshold segmentation. Download full text:Check if you have access through your login credentials or your institution Username Password

A novel approach to background subtraction in contrast-enhanced dual-energy digital mammography with commercially available mammography devices: Polychromaticity correction.

Contrast-enhanced digital mammography is an image subtraction technique that is able to improve the detectability of lesions in dense breasts. One of the main sources of error, when the technique is performed by means of commercial mammography devices, is represented by the intrinsic polychromaticity of the x-ray beams. The aim of the work is to propose an iterative procedure, which only assumes the knowledge of a small set of universal quantities, to take into account the polychromaticity and correct the subtraction results accordingly. In order to verify the procedure, it has been applied to an analytical simulation of a target containing a contrast medium and to actual radiographs of a breast phantom containing cavities filled with a solution of the same medium. The reconstructed densities of contrast medium were compared, showing very good agreement between the theoretical predictions and the experimental results already after the first iteration. Furthermore, the convergence of the iterative procedure was studied, showing that only a small number of iterations is necessary to reach limiting values. The proposed procedure represents an efficient solution to the polychromaticity issue, qualifying therefore as a viable alternative to inverse-map functions.

Automated Technique to Measure Noise in Clinical CT Examinations.

The purpose of this study was to develop and validate an automated method to measure noise in clinical CT examinations. An automated algorithm was developed to measure noise in CT images. To assess its validity, the global noise level was compared with image noise measured using an image subtraction technique in an anthropomorphic phantom. The global noise level was further compared with image noise values from clinical patient CT images obtained by an observer study. Finally, the clinical utility of the global noise level was shown by assessing variability of image noise across scanner models for abdominopelvic CT examinations performed in 2358 patients. The global noise level agreed well with the phantom-based and clinical image-based noise measurements, with an average difference of 3.4% and 4.7% from each of these measures, respectively. No significant difference was detected between the global noise level and the validation dataset in either case. It further indicated differences across scanners, with the median global noise level varying significantly between different scanner models (15-35%). The global noise level provides an accurate, robust, and automated method to measure CT noise in clinical examinations for quality assurance programs. The significant difference in noise across scanner models indicates the unexploited potential to efficiently assess and subsequently improve protocol consistency. Combined with other automated characterization of imaging performance (e.g., dose monitoring), the global noise level may offer a promising platform for the standardization and optimization of CT protocols.

A Driver-Assistance System for Large Vehicles Based on Pedestrian and Vehicle Detection

Apply driving assistance system to vehicles can significantly reduce accidences and thus attracts much interest nowadays. However, most existing systems are designed specifically for small vehicles and always suffer from drawbacks such as low pedestrian and vehicle detection accuracy and long detection time. To solve these issues, in this paper we develop a driver assistance system based on radar and camera, which can be applied to large vehicles and can detect vehicle and pedestrian simultaneously. Specifically, we combine the image subtraction technique and histogram algorithm to perform pedestrian and vehicle detection to improve detection rate. What’s more, this system can automatically determine whether the object is inside a danger region. If yes, an associated warning signal will be triggered to alarm the driver. Experimental results show that the successful detection rate is sufficiently good and the detecting speed is fast enough to timely alarm the driver to avoid accidents.

Advanced Moving Object Detection by Using K-means Algorithm

Moving Object Detection systems have long been in use to look at security sensitive areas. The manufacture of video investigating systems sensible desires fast, reliable and durable algorithms for moving object detection classification pursuit and activity analysis. Moving object detection is that the essential step for extra analysis of video. It handles segmentation of moving objects from stationary background objects. Object classification step categorizes detected objects into preened classes like human, vehicle, animal, clutter, etc. it's a necessity to inform apart objects from each other therefore on trace and analyse their actions reliably. In previous system we have got performed background subtraction by victimization clever Edge Detection. In clever Edge Detection technique we tend to tend to square measure taking 2 photos for comparison those square measure background image and foreground image. Previous strategies for object detection square measure methodology along side object detectors image segmentation and Background subtraction. Our methodology aims to section objects supported motion info and it contains a part of background modelling. In the previous strategies we tend to tend to square measure conducting background subtraction only for photos. For this we tend to tend to projected an image component wise background modelling and subtraction technique mistreatment multiple choices. Hence, throughout this color, gradient and Hear-Like choices square measure integrated to handle the variation element. Thus, motion segmentation and background subtraction square measure the foremost connected topics to the current paper.

SU-E-T-70: Commissioning a Multislice CT Scanner for X-Ray CT Polymer Gel Dosimetry

Purpose: To commission a multislice computed tomography (CT) scanner for fast and reliable readout of radiation therapy (RT) dose distributions using CT polymer gel dosimetry (PGD). Methods: Commissioning was performed for a 16-slice CT scanner using images acquired through a 1L cylinder filled with water. Additional images were collected using a single slice machine for comparison purposes. The variability in CT number associated with the anode heel effect was evaluated and used to define a new slice-by-slice background image subtraction technique. Image quality was assessed for the multislice system by comparing image noise and uniformity to that of the single slice machine. The consistency in CT number across slices acquired simultaneously using the multislice detector array was also evaluated. Finally, the variability in CT number due to increasing x-ray tube load was measured for the multislice scanner and compared to the tube load effects observed on the single slice machine. Results: Slice-by-slice background subtraction effectively removes the variability in CT number across images acquired simultaneously using the multislice scanner and is the recommended background subtraction method when using a multislice CT system. Image quality for the multislice machine was found to be comparable to that of the single slice scanner.more » Further study showed CT number was consistent across image slices acquired simultaneously using the multislice detector array for each detector configuration of the slice thickness examined. In addition, the multislice system was found to eliminate variations in CT number due to increasing x-ray tube load and reduce scanning time by a factor of 4 when compared to imaging a large volume using a single slice scanner. Conclusion: A multislice CT scanner has been commissioning for CT PGD, allowing images of an entire dose distribution to be acquired in a matter of minutes. Funding support provided by the Natural Sciences and Engineering Research Council of Canada (NSERC)« less

A new precise mass for the progenitor of the Type IIP SN 2008bk★†‡

The progenitor of the Type IIP SN 2008bk was discovered in pre-explosion g'r'i'IYJHKs images, acquired with European Southern Observatory Very Large Telescope FORS, HAWK-I and ISAAC instruments and the Gemini GMOS-S instrument. The wealth of pre-explosion observations makes the progenitor of this SN one of the best studied, since the detection of the progenitor of SN1987A. Previous analyses of the properties of the progenitor were hampered by the limited quality of the photometric calibration of the pre-explosion images and the crowded nature of the field containing the SN. We present new late-time observations of the site of SN2008bk acquired with identical instrument and filter configurations as the pre-explosion observations, and confirm that the previously identified red supergiant star was the progenitor of this SN and has now disappeared. Image subtraction techniques were used to conduct precise photometry of the now missing progenitor, independently of blending from any nearby stars. The nature of the surrounding stellar population and their contribution to the flux attributed to the progenitor in the pre-explosion images are probed using HST WFC3 UVIS/IR observations. In comparison with MARCS synthetic spectra, we find the progenitor was a highly reddened RSG with luminosity log (L/Lsun)=4.84+/-0.11, corresponding to an initial mass of Minit=12.9+/-1.7Msun. The temperature of the progenitor was hotter than previously expected for RSGs (T ~ 4330K), but consistent with new temperatures derived for RSGs using SED fitting techniques. We show that there is evidence for significant extinction of the progenitor, possibly arising in the CSM; but that this dust yields a similar reddening law to dust found in the ISM (E(B-V)=0.77 with Rv=3.1). [Abridged]

A late-time view of the progenitors of five Type IIP supernovae

The acquisition of late-time imaging is an important step in the analysis of pre-explosion observations of the progenitors of supernovae. We present late-time HST ACS WFC observations of the sites of five Type IIP SNe: 1999ev, 2003gd, 2004A, 2005cs and 2006my. Observations were conducted using the F435W, F555W and F814W filters. We confirm the progenitor identifications for SNe 2003gd, 2004A and 2005cs, through their disappearance. We find that a source previously excluded as being the progenitor of SN 2006my has now disappeared. The late-time observations of the site of SN 1999ev cast significant doubt over the nature of the source previously identified as the progenitor in pre-explosion WFPC2 images. The use of image subtraction techniques yields improved precision over photometry conducted on just the pre-explosion images alone. In particular, we note the increased depth of detection limits derived on pre-explosion frames in conjunction with late-time images. We use SED fitting techniques to explore the effect of different reddening components towards the progenitors. For SNe 2003gd and 2005cs, the pre-explosion observations are sufficiently constraining that only limited amounts of dust (either interstellar or circumstellar) are permitted. Assuming only a Galactic reddening law, we determine the initial masses for the progenitors of SNe 2003gd, 2004A, 2005cs and 2006my of 8.4+/-2.0, 12.0+/-2.1, 9.5(+3.4,-2.2) and 9.8+/-1.7Msun, respectively.

Dinâmica do uso e cobertura da terra no sudeste de Roraima utilizando técnicas de detecção de mudanças

A ocupação e consolidação do território na Amazônia apresentam diferentes características relacionadas à dinâmica das conversões de uso e cobertura da terra, que podem ser analisadas utilizando imagens orbitais de sensoriamento remoto. O objetivo do presente trabalho foi avaliar os produtos de detecção de mudanças gerados por análise de vetor de mudança (AVM) e subtração de imagens, a partir de imagens-fração derivadas das imagens ópticas TM/Landsat, para o estudo das conversões de uso e cobertura da terra presentes em área de colonização agrícola na região sudeste de Roraima. Analisaram-se as imagens de mudança provenientes da aplicação do AVM (magnitude, alfa e beta) e da subtração das imagens-fração (solo, sombra e vegetação) quanto à sua capacidade de identificar e discriminar as conversões existentes, de acordo com levantamento de campo. Foram testados dois algoritmos de classificação de imagens do tipo supervisionado, Bhattacharyya e Support Vector Machine. Foram feitos agrupamentos para otimizar a identificação das conversões nas classificações testadas. Houve melhor desempenho do classificador por regiões Bhattacharyya na discriminação das conversões. A utilização das imagens-diferença das frações como informação de entrada para o classificador apresentou qualidade de classificação muito boa ou excelente, sendo superior às classificações utilizando os produtos AVM, isoladamente ou em conjunto com as imagens-diferença.

Logarithmic fringe-adjusted joint transform correlation

An improved fringe-adjusted joint transform correlation (FJTC) technique is proposed, which employs a new real-valued filter, called the logarithmic fringe-adjusted filter. The Fourier-plane image subtraction technique is applied to the joint power spectrum before applying the inverse Fourier transform to generate better correlation output. The proposed technique yields better correlation output compared to alternate optical pattern recognition techniques when the target is embedded in noise-corrupted input scenes. Test results are presented to verify the performance of the proposed technique.