Spectral Matching Technique Research Articles

Spectral band-shifting of multispectral remote-sensing reflectance products: Insights for matchup and cross-mission consistency assessments

Comparing or integrating remote-sensing reflectance, Rrsλsr−1, data from multispectral sensors is hindered by differences in their nominal bands and relative spectral-response functions. Similarly, assessing satellite-to-in situ-matchup assessments of Rrs using autonomous ground radiometers, such as the Ocean Color component of the Aerosol Robotic Network (AERONET-OC), faces the same challenges. Therefore, spectral band-shifting techniques are required to approximate Rrs in spectral bands that are mutually unavailable. We present a spectral-matching technique (SMTH) using a novel look-up-table (LUT) generated from Rrs obtained from the Hyperspectral Imager for the Coastal Ocean (HICO) sensor. This LUT consists of nearly 6.3 million unique Rrs spectra, processed from 8893 Level-2 HICO scenes. An extensive in situ hyperspectral dataset (n = 8289) was used to compare the performance of SMTH with three commonly used techniques, namely Melin and Sclep (2015) “MS-QAA” model, linear (LNR) and cubic spline (CS) interpolations. The comprehensive evaluation of eight sensors using in situ dataset revealed that the SMTH has significantly better overall accuracy with respect to spectral band-shifting than the existing approaches. The Bias was improved 7-fold, whereas the root-mean-square difference (RMSD) and mean absolute difference (MAD) were ∼ 15–60% lower. Even so, each model exhibits outstanding performance in certain bands. For instance, the LNR model excels in the 380 nm band, while the MS-QAA emerges as the optimal choice for the 400 and 412 nm bands. SMTH outperforms other models in the green-red region, notably above 600 nm, where most existing ocean-color sensors have a limited number of spectral bands. Despite this variability, all models, showcase satisfactory performance in the 443–560 nm region. Significantly, both SMTH and LNR demonstrated a 100% retrieval rate, the ratio of band-shifted samples to the input samples. In contrast, MS-QAA and CS returned invalid values for 7% and 39% of the input samples, respectively. Further evaluation of regional, global, and composite satellite data suggests that the trophic state significantly influences the model performance. The MS-QAA model exhibited the smallest differences within the oligotrophic waters, characterized by low chlorophyll-a concentrations. In contrast, the SMTH model demonstrates the lowest differences in mesotrophic/eutrophic waters and regions subject to harmful algal blooms. While HICO primarily sampled coastal waters, estuaries, and shallow regions from mid- to low latitudes, there is an opportunity to enhance the representativeness of our LUT by incorporating open-ocean and high-latitude Rrs spectra from the upcoming hyperspectral missions, such as NASA's Plankton, Aerosol, Clouds, ocean Ecosystem (PACE).

New generalized ANN-based hybrid broadband response spectra generator using physics-based simulations

Estimation of the seismic risk associated with infrastructures requires site-specific seismic hazard studies. Further, for nonlinear time history analysis, one requires broadband ground motion. In modern times, physics-based simulations (PBS) for deriving the ground motion for future earthquakes have been considered. The PBS helps decrease the uncertainties related to hazard estimation compared to ground motion prediction equations. The PBS methods have a specific frequency threshold limit resulting from high computational demand. Hence, hybrid methods are required to attain broadband spectra for the simulated ground motion. This study uses a new artificial neural network (ANN)-based model to generate broadband ground motion spectra using the low-frequency spectral acceleration from PBS, source, path, and site parameters as input variables. A detailed parametric study and performance evaluation was made to identify the optimal input parameters in conjunction with the best-suited ANN architecture. The performance of the ANN model is demonstrated for Iwate (\(M_w\) 6.9, 2008) earthquake. We found that the predicted values from the developed ANN model agree with the recorded data. Furthermore, time histories are generated using the spectral ordinate matching technique from the estimated broadband spectra.

Local Site effects for ground motion acceleration and amplification at Bahrah, Saudi Arabia.

The soil conditions variability at site strongly influence ground motions during earthquakes. The disastrous earthquakes have shown that the local site conditions are the essential factors that impact lsurficial ground motions. In present study, local site effects are evaluated for ground motion acceleration and amplification at Bahrah. The town is situated on which is covered by quaternary alluvial wadi deposits. The ground motion time series are obtained through Spectral matching technique. is utilized to generate well matched ground motion time series based on the results of the PSHA and the deaggregation process. The ground motion time series and shallow Geophysical data are utilized to carry out One-dimensional simulation is carried out for equivalent linear seismic response analyses for soil layers. Results of One-dimensional site response analysis are interpolated to generate maps that account for ground motion accelerations and amplifications at top of the soil for selected spectral periods (PGA, 0.1, 0.2 and 2) for 475 years return period. The maps show the ground shaking rather than the probability of damage to buildings. The maximum values of amplification ranges upto 3.46 and acceleration upto 0.86 g. The undulation of bed rock topography and existence of deep soft sediments are reflected considerably on the results of the study area. The surface ground motion maps show that the seismic hazard level in Bahrah is moderate.

Analysis on Spectral Matching of Biochemical Component for Rice

The protein, starch and amylose are three important indexes to characterize rice quality. The starch, crude protein and amylose of rice were extracted by experiments. The hyperspectral reflectance of starch, crude protein and amylose, their mixed samples and rice samples were determined by a ASD FieldSpec Pro FR™ The spectral characteristics of starch, crude protein, amylose and their correlation with component content were analyzed by using spectral matching technique and multivariate statistical method. The results showed that the spectra of three biochemical components were significantly different, and the spectral peaks and valleys of the mixed samples showed “red shift” or “blue shift”. The contents (%) of crude protein, starch and amylose in rice flour were significantly related to the absorption area S between 2020nm and 2235nm on their spectral curve. The results showed that the hyperspectral method could be used to estimate the contents of crude protein, starch and amylose content in rice, and then to detect rice quality.

Site-specific seismic hazard levels at the economic zone of Duqm, Oman

AbstractA site-specific probabilistic seismic hazard assessment (PSHA) was achieved in the area of special economic zone authority of Duqm, involving hazard evaluation at the bedrock conditions and assurance of potential site influence on seismic ground motion at the bedrock. Appropriate source and ground-motion prediction models were selected and seismic hazards were identified by means of 5% damped Uniform Hazard Spectra (UHS) for three return periods of 475, 975, and 2475 years. A logic-tree algorithm was used to study the influence of the epistemic uncertainties on the source models, earthquake recurrency and maximum magnitude, along with ground-motion prediction equations (GMPEs). The local geology effects were characterized by fundamental resonance frequency (Fo) using the horizontal-to-vertical spectral ratio technique and the soil amplification factors. The effects of soil were assessed using SHAKE91 for soil parameters defined by 55 geotechnical boreholes in conjunction with surveys of 2D multichannel analysis of surface waves (MASW) at 90 sites. Scaling was performed for selected strong-motion applying spectral matching technique to be used at the soil column bottom. Selection of such records is based on scenarios characterized by deaggregation of the PSHA results on the bedrock tops. The Duqm area mostly features low amplifications, below 1.3 for the considered spectrum. Surface ground-motion maps show low hazard values with Peak Ground Accelerations (PGA) vary between about 2 and 5% g for a 475-year return period. Although several sites are assessed to be susceptible to liquefy, liquefaction analyses indicate that surface ground motions for a 475-year return period are insufficient to produce liquefaction.

Generating high spectral consistent endurance time excitations by a modified time-domain spectral matching method

Endurance time acceleration functions (ETAFs) are the intensified acceleration time series whose spectral responses match time-varying targets in order to evaluate multiple-level structural seismic performances with few dynamic analyses. However, the matching precision of the ETAFs generated by the existing frequency-domain method is not satisfactory enough and thus still needs three or more ETAFs to reach an acceptable accuracy. In this study, a high-precision and efficient ETAF generation method is proposed to obtain highly spectral consistent ETAFs. Considering the time-varying characteristic of ETAFs, the time-domain spectral matching technique is modified and extended to improve the spectral fitness of ETAFs for multiple durations. Taking the multi-duration response spectra as the matching targets, the matching procedure is conducted, and several ETAFs are generated in accord with seismic design codes. The matching precision is controlled by a specified tolerance and the number of iterations. The results show that the proposed method can successfully generate high-accuracy ETAFs, so that a sufficient accuracy of seismic performance analysis can be reached with only one single ETAF. The ETAFs generated by the proposed method are compared with those generated by an existing method in the matching precision, computational time, time variation trend, and the ETAF duration. Compared with the existing method, the proposed method can achieve remarkably higher matching precision and requires considerably less computational time, especially for long-duration ETAFs. The proposed method can also match average acceleration spectra from real ground motions and accurately predict the seismic responses in the structural nonlinear analysis.

Synthetic stochastic ground motions compatible with the Chilean seismic hazard

This paper develops a record-based stochastic ground motion model for the Chilean Subduction zone that generates ground motions compatible with the seismic hazard (represented by a local Ground Motion Predictive Equation GMPE) for both interplate and intraslab mechanism and considering rock soil conditions. The stochastic ground motion is obtained by the modulation of white-noise sequence in both time and spectral domain applying non-stationary filters. Compatibility is obtained by a proper tuning of predictive relationships, which offers a relation between seismological parameters and the driven parameters in the non-stationary filters. This process demands an intensive computational optimization problem where the parameters in the predictive relationships are found such that the stochastic ground motions generated match with the GMPE. The computational burden is decreased by the use of a Kriging metamodel which provides a high-fidelity approximation of the mean response spectra for different natural structural periods and the predictive relationship parameters. Once the predictive relationships are adjusted, the results are validated by comparing the prediction of mean spectral acceleration response from the GMPE with the prediction using the stochastic ground motion model. The Kriging model is built once and could be used to repeat the optimization for new GMPEs and predictive relationships (as a result of an updating process to incorporate new important seismic events) within a relatively low computational cost. In addition, a post-adjustment methodology is proposed to improve the results, using a scaling and spectral matching technique.

Crop type identification and spatial mapping using Sentinel-2 satellite data with focus on field-level information

Accurate monitoring of croplands helps in making decisions (for insurance claims, crop management and contingency plans) at the macro-level, especially in drylands where variability in cropping is very high owing to erratic weather conditions. Dryland cereals and grain legumes are key to ensuring the food and nutritional security of a large number of vulnerable populations living in the drylands. Reliable information on area cultivated to such crops forms part of the national accounting of food production and supply in many Asian countries, many of which are employing remote sensing tools to improve the accuracy of assessments of cultivated areas. This paper assesses the capabilities and limitations of mapping cultivated areas in the Rabi (winter) season and corresponding cropping patterns in three districts characterized by small-plot agriculture. The study used Sentinel-2 Normalized Difference Vegetation Index (NDVI) 15-day time-series at 10 m resolution by employing a Spectral Matching Technique (SMT) approach. The use of SMT is based on the well-studied relationship between temporal NDVI signatures and crop phenology. The rabi season in India, dominated by non-rainy days, is best suited for the application of this method, as persistent cloud cover will hamper the availability of images necessary to generate clearly differentiating temporal signatures. Our study showed that the temporal signatures of wheat, chickpea and mustard are easily distinguishable, enabling an overall accuracy of 84%, with wheat and mustard achieving 86% and 94% accuracies, respectively. The most significant misclassifications were in irrigated areas for mustard and wheat, in small-plot mustard fields covered by trees and in fragmented chickpea areas. A comparison of district-wise national crop statistics and those obtained from this study revealed a correlation of 96%.

Indoor Global Localization Using Depth-Guided Photometric Edge Descriptor for Mobile Robot Navigation

This paper suggests a new landmark descriptor for indoor mobile robot navigation with sensor fusion and a global localization method using it. In previous research on robot pose estimation, various landmarks such as geometric features, visual local-invariant features, or objects are utilized. However, in real-world situations, there is a possibility that distinctive landmarks are insufficient or there are many similar landmarks repeated in indoor environment, which makes accurate pose estimation difficult. In this work, we suggest a new landmark descriptor, called depth-guided photometric edge descriptor (DPED), which is composed of superpixels and approximated 3D depth information of photometric vertical edge. With this descriptor, we propose a global localization method based on coarse-to-fine strategy. In the coarse step, candidate nodes are found by place recognition using our pairwise constraint-based spectral matching technique, and the robot pose is estimated with a probabilistic scan matching in the fine step. The experimental results show that our method successfully estimates the robot pose in the real-world tests even when there is a lack of distinctive features and objects.

Color normalization of faded H&E-stained histological images using spectral matching

Histological samples stained with hematoxylin-eosin (H&E) are commonly used by pathologists in cancer diagnoses. However, the preparation, digitization, and storage of tissue samples can lead to color variations that produce poor performance when using histological image processing techniques. Thus, normalization methods have been proposed to adjust the color of the image. This can be achieved through the use of a spectral matching technique, where it is first necessary to estimate the H&E representation and the stain concentration in the image pixels by means of the RGB model. This study presents an estimation method for H&E stain representation for the normalization of faded histological samples. This application has been explored only to a limited extent in the literature, but has the capacity to expand the use of faded samples. To achieve this, the normalized images must have a coherent color representation of the H&E stain with no introduction of noise, which was realized by applying the methodology described in this proposal. The estimation method presented here aims to normalize histological samples with different degrees of fading using a combination of fuzzy theory and the Cuckoo search algorithm, and dictionary learning with an initialization method for optimization. In visual and quantitative comparisons of estimates of H&E stain representation from the literature, our proposed method achieved very good results, with a high feature similarity between the original and normalized images.

Rapid Screening of Free Oligosaccharides in Human and Animal Milks by HILIC-MS/MS and Tandem Mass Spectral Library (P13-033-19)

ObjectivesMammalian milk oligosaccharides (MMOs) from human and farm animals have been of great interest because of their functional application in food nutrition. However, the biological significance of the variation in proportions of MMOs among milks is poorly understood. MMO concentration (0.05 - 0.3 g/L) in mature animal milk is >20 fold lower than human milk oligosaccharides (HMOs) (12 g/L) [1]. Hence, screening techniques are necessary for the structural characterization of MMOs in milk. This study characterizes and compares chemical structures derived from tandem mass spectra of free oligosaccharides in the milk of human and animals for the development of a MS library for MMOs. MethodsIsolation and purification of MMOs by HILIC-MS analysis as described [1]. Precursor and product ion tolerances were <10 ppm when searched against the NIST 17 Tandem MS reference library coupled with the recently released HMO library using the NIST MS Search v2.3 software. These were used to annotate unknown precursor mass using peak areas of the free and annotated MMO in the milk of human, bovine, goat, buffalo and African lion. ResultsA variety of unknown oligosaccharides were derived from results of HILIC-MS analysis of various milks. This comparative study of MMO composition resulted in the identification of 144 MMOs, of which 74 are derived from human milk. The number of identified compounds in the milk of lion (60) were different than those in other mammals; human, bovine (21), buffalo (43) and goat (44). MS/MS analysis of sialylated MMOs distinguished Neu5Gc from Neu5Ac. The mass spectral matching technique efficiently identifies MMO structures. Novel MMOs in milk samples were identified. African lion and buffalo milk had the fewest number of MMOs similar to HMOs. Note that type II linkage Gal(β1–4) is primarily found in animal milk compared with type I Gal(β1–3), typical in HMOs.[1] J. British Nutrition, Albrecht et al., 2014[2] J. Analytical Chemistry, Remoroza et al., 2018 ConclusionsDetailed analysis of the chemical structures identified in this study documents significant variability of MMOs in milk of animals with respect to human milk. Funding SourcesNIST.

Site Response Analysis of Deep Sedimentary Deposits Using Electrical Resistivity Logging; Case Study: Guilan Province, Iran

Local geology of site and its properties can influence the input seismic wave specifications dramatically such as frequency content and duration while passing through soil stratums, making it inevitable to perform site-specific ground response analysis. For such analysis, soil’s dynamic properties including shear wave velocity (Vs) and shear modulus (G) are required, which are usually obtained using laboratory or field tests, commonly too expensive and time consuming for regions having deep sedimentary deposits. Electrical resistance of ground can be put into practice as a cost-effective alternative in assessing soils dynamic properties in order to be utilized in site response analysis, since the subsurface materials such as soil and rock have unique electrical properties. In this study, the feasibility of site response analysis using electrical logging has been evaluated using field data measurements of electrical resistivity and borehole logging through Guilan province, which is located on the southern shoreline of the Caspian Sea and in a region with high seismicity having deep sedimentary deposits. Nonlinear site response analysis as well as equivalent linear one is carried out in order to obtain the spectral response of the region, separately for the eight data points of the study. The acceleration time histories were synthesized using spectral matching technique integrating with probabilistic seismic hazard analysis. According to the results, the NL and EQL response and design spectrums, which are obtained in this study, show decent agreement with Iran’s 2800 seismic design spectrum, indicating acceptable performance of site response analysis using electrical resistivity logging.

An Efficient Method for Considering the Directionality Effect of Earthquakes on Structures

ABSTRACT Recent research have proven the importance of considering the directionality effect on the expected seismic damage of structures. However, it demands a high computational effort if the nonlinear dynamic analysis (NLDA) is used to estimate the seismic response. This paper presents a simplified approach to obtain peak response parameters for a building subjected to bi-directional ground motions considering the directionality effect. To do so, the maximum and median response spectra, considering all the non-redundant response spectra, of several ground motion pairs are calculated. Afterwards, a spectral matching technique is applied to these spectra and new acceleration components are obtained. A series of NLDA are performed with these new components and the roof displacement and base shear values are calculated. These results are compared with the maximum and median values, calculated by performing a series of NLDA, after rotating the earthquakes records by considering increments of 1° in the interval 0°–180°. The results agree with both approaches validating the efficiency of the simplified proposed approach.

Site-specific earthquake ground motion parameters at the southeastern part of Muscat, Sultanate of Oman

The site-specific earthquake ground motion parameters were presented for the southeastern part of Muscat governorate, including amplification factor at different periods and the values of PGA and spectral accelerations at the surface. The study starts with assessment of the seismic hazard at bedrock level using the probabilistic approach. This assessment was preformed considering an updated earthquake catalogue. The outputs of the probabilistic seismic hazard were uniform hazard spectra for return periods of 475,975 and 2475 years. Spectral matching technique was applied to define the compatible ground motion time series based on the outputs of the probabilistic approach and the deaggregation process. The representative's dynamic soil profiles were determined using the in-situ measurements of compressional and shear waves. The effects of soil deposits on the propagated ground motions time series was evaluated using the equivalent linear analysis in the frequency domain. The final results clarified that, the fundamental site period at the middle coastal parts of the area has the largest values (0.2–0.276 s). The maximum amplification factors found to be 2.76, 2.36, and 2.8 for the periods of PGA, 0.1 s, and 0.2 s, respectively. The values of PGA and spectral accelerations at the surface level are also provided.

Type II Supernova Spectral Diversity. I. Observations, Sample Characterization, and Spectral Line Evolution*

Abstract We present 888 visual-wavelength spectra of 122 nearby type II supernovae (SNe II) obtained between 1986 and 2009, and ranging between 3 and 363 days post-explosion. In this first paper, we outline our observations and data reduction techniques, together with a characterization based on the spectral diversity of SNe II. A statistical analysis of the spectral matching technique is discussed as an alternative to nondetection constraints for estimating SN explosion epochs. The time evolution of spectral lines is presented and analyzed in terms of how this differs for SNe of different photometric, spectral, and environmental properties: velocities, pseudo-equivalent widths, decline rates, magnitudes, time durations, and environment metallicity. Our sample displays a large range in ejecta expansion velocities, from ∼9600 to ∼1500 km s−1 at 50 days post-explosion with a median value of 7300 km s−1. This is most likely explained through differing explosion energies. Significant diversity is also observed in the absolute strength of spectral lines, characterized through their pseudo-equivalent widths. This implies significant diversity in both temperature evolution (linked to progenitor radius) and progenitor metallicity between different SNe II. Around 60% of our sample shows an extra absorption component on the blue side of the P-Cygni profile (“Cachito” feature) between 7 and 120 days since explosion. Studying the nature of Cachito, we conclude that these features at early times (before ∼35 days) are associated with Si ii , while past the middle of the plateau phase they are related to high velocity (HV) features of hydrogen lines.

Label-free quantification of meat proteins for evaluation of species composition of processed meat products

This study evaluated the application of label-free, relative quantification of highly processed meat proteins to authenticate processed meat products. Quantitation was based on proteins for which heat-stable and species-specific peptide markers had been detected. Using nano-LC-QTOF-MS/MS, 20 new, heat-stable peptide markers unique to chicken, duck and goose were identified, with significant scores. The method enabled detection of 1%(w/w) of chicken and 1%(w/w) pork in a mixture of the meat of three species, as well as 0.8%(w/w) beef proteins in commercial poultry frankfurters. The proteins’ abundance was computed using a spectral matching technique, termed the absolute protein expression (APEX) proteomics tool. This method includes a correction factor for each protein, based on the peptide MS detection probabilities, which are influenced by the physicochemical properties of the peptide. Considerable differences in abundance of myofibrillar and sarcoplasmic proteins were observed between samples and illegal proportions of ingredients were discovered.

Spectral similarity approach for mapping turbidity of an inland waterbody

Turbidity is an important quality parameter of water from its optical property point of view. It varies spatio-temporally over large waterbodies and its well distributed measurement on field is tedious and time consuming. Generally, normalized difference turbidity index (NDTI), or band ratio, or regression analysis between turbidity concentration and band reflectance, approaches have been adapted to retrieve turbidity using multispectral remote sensing data. These techniques usually provide qualitative rather than quantitative estimates of turbidity. However, in the present study, spectral similarity analysis, between the spectral characteristics of spaceborne hyperspectral remote sensing data and spectral library generated on field, was carried out to quantify turbidity in the part of Chilika Lake, Odisha, India. Spatial spectral contextual image analysis, spectral angle mapper (SAM) technique was evaluated for the same. The SAM spectral matching technique has been widely used in geological application (mineral mapping), however, the application of this kind of techniques is limited in water quality studies due to non-availability of reference spectral libraries. A spectral library was generated on field for the different concentrations of turbidity using well calibrated instruments like field spectro-radiometer, turbidity meter and hand held global positioning system. The field spectra were classified into 7 classes of turbidity concentration as <5, 5–10, 10–15, 15–25, 25–45, 45–100 and >100NTU for analysis. Analysis reveal that at each location in the lake under consideration, the field spectra matched with the image spectra with SAM score of 0.8 and more. The observed turbidity at each location was also very much falling in the estimated turbidity class range. It was observed that the spectral similarity approach provides more quantitative estimate of turbidity as compared to NDTI.

SEISMIC TIME-HISTORY GROUND-MOTIONS FOR A SPECIFIC SITE IN JAKARTA

Indonesia has developed new seismic building code based on risk-targeted ground-motions adopting 1 % probability of building collapse in 50 years. The new seismic design criterion, which is presented in the code, have combined both seismic hazard and building fragility. For performance-based analysis of high-rise buildings, a complex non-linear time-history analysis is needed. This paper presents results of study on development of the time-history with emphasing on procedure of developing pairs of time-history at ground surface for spesific site in Jakarta with reference to 2012 International Building Codes and ASCE-SEI-7-10. The study involves generation of time-history from reference base-rock through site-response analysis to ground surface. Development of time-history at ground surface with a procedure involving Square Root of the Sum of the Square method (SRSS) in order to reasonably scaled time-histories through spectral matching technique is presented herein. The matched time-histories are developed from various strong-motion records representing different earthquake sources dominant to control the site evaluated from de-aggregation within seismic hazard analysis. This work also adopts baseline corrections in which velocity and displacement components of matched time-histories can be drifted to zero at the end of recorded seismic time.

A search for Mg-poor stars using LAMOST survey data

Most Galactic metal-poor stars exhibit enhanced α-abundances (e.g. [Mg/Fe] ∼ +0.4) according to previous studies of stellar chemical compositions. However, a handful of metal-poor stars with large deficiencies in Mg (e.g. [Mg/Fe] ∼ −0.2) show severe departures from this α-enhancement trend. The sub-solar [Mg/Fe] ratios of these anomalous stars indicate that they possess different chemical enrichment histories than the majority of Galactic metal-poor stars. In previous work, we presented a method to select Mg-poor metal-poor stars from low-resolution SDSS spectra based on a spectral matching technique. In this paper, a similar method is applied to low-resolution (R ∼ 1800) LAMOST spectra. Stellar [Mg/Fe] abundances are determined by using stellar parameters delivered by the LAMOST Data Release 2 catalog. From a sample of ∼ 60 000 stars with atmospheric parameters in the range Teff = [5500, 6500] K and [Fe/H] = [−2.4, +0.5], we select 15 candidate Mg-poor metal-poor stars.

Spectral technique to recognise occluded objects

When recognising partially visible objects in a scene, a good global decision should be made based on locally gathered features for their recognition, since global information is no longer reliable. This local-to-global nature of occlusion recognition leads us to spectral matching technique. Unfortunately, conventional spectral matching is not desirable for noisy data set from a cluttered scene. In this study, a top-down procedure is introduced into a standard spectral matching for the recognition of occluded objects. Feature points are firstly evaluated and associated with object(s) of interest. Subsequently, geometrical consistency is enforced to find correct correspondences among the candidate matches with high association scores. Based on this two-stage strategy, both appearance and geometric information are taken into consideration. Our algorithm is implemented for both 2D and 3D occluded objects recognition under different occlusion rates. It is shown that the improvement has been made for spectral correspondence algorithm to recognise occluded objects and it has a comparable recognition rate with the state-of-the-art recognition methods.