Equalization Step Research Articles

Hydrogen production from low pressure coke oven gas by vacuum pressure swing adsorption

Hydrogen is a major component of coke oven gas (COG) and can be used in gas-based direct reduction iron processes to help the steel industry achieve the carbon peaking and carbon neutrality goals. However, the high compression power consumption is the main drawback of the current PSA cycle since the COG needs to be compressed from atmospheric pressure to ∼18 bar to achieve a hydrogen production with purity >99.9% and recovery < 85%. Here in this study, we experimentally demonstrate by using a 4-bed 12-step lab-scale VPSA rig filled with activated carbon RB3 and can obtain a hydrogen product with a purity of 99.67% and a recovery of 91.97% at a feed pressure of only 5.17 bar. We then constructed a non-isothermal non-adiabatic VPSA model using our in-house code and validated the model against experimental breakthrough and VPSA cycles. Parametric optimization produced a H2 product of 99.995% purity and 92.29% recovery at a slightly increased adsorption pressure of 6 bar and a vacuum pressure of 0.02 bar with 10.21 mol.H2/kg.ads/hr productivity and 7.09 kJ/mole.H2 specific power. We also confirmed that light product purge at vacuum pressure can effectively improve the H2 purity and the gas flow direction of the pressure equalization step has a significant effect on the mass transfer front. Our research presents the success of low-pressure hydrogen production from COG, which will greatly accelerate the transformation of COG utilization and promote the decarbonization of the iron and steel industry.

Lipoabdominoplasty: Comparing Ultrasound-Assisted and Power-Assisted Techniques

Introduction: Optimizing the abdomen aesthetic appearance may combine liposculpture, abdominoplasty, and postsurgical noninvasive body sculpting. The abdominoplasty traditional technique highlights abdominal flap undermining. The Avelar or Saldana lipoabdominoplasty’s technique modifications use liposuction and the absence of undermining of the abdominal wall flap. This method maintains abdominal wall vascularization and lessens complications. Two commonly employed liposuction techniques are power-assisted and ultrasound-assisted liposuction. Combining power-assisted technology with the Separation, Aspiration, Fat Equalization (SAFE) liposuction process has improved aesthetic results and reduced complications. Separation, Aspiration, Fat Equalization liposuction process enrolls separation, aspiration, and fat equalization steps. Ultrasound-assisted liposuction advantages include high-definition body sculpting through maximum fat removal and skin tightening with less blood loss and viable fat for grafting. This clinical study evaluated a comprehensive surgical protocol for lipoabdominoplasty designed to minimize complications. In addition, the study assessed aesthetic outcome and complication differences comparing the use of ultrasound-assisted versus power-assisted liposuction. Materials and Methods: This is a retrospective study in a single surgeon’s private cosmetic practice in 2 practice locations in patients undergoing a modified lipoabdominoplasty technique over a 2-year period. Results: Modified lipoabdominoplasty combining power-assisted technology with SAFE liposuction (n = 30) compared to those using ultrasound-assisted liposuction (n = 20) revealed similar complication rates. Surgeon observation revealed better skin contour smoothness, more abdominal definition and skin tightening with less bruising when using ultrasound liposuction. The comprehensive surgical protocol designed to minimize perioperative complications was implemented on each patient and resulted in no medical errors and a low major and minor complication rate. Conclusions: The lipoabdominoplasty surgical protocol provides surgeon’s comprehensive preoperative, intraoperative, and postoperative guidelines to minimize complications. Higher body mass index increased the complication rate. The aesthetic outcome using ultrasound-assisted liposuction appeared to yield better aesthetic sculpted appearance with less bruising compared to power-assisted technology.

Experimental performance analysis of vacuum pressure swing adsorption air separation process under plateau special conditions

ABSTRACT A small scale (~270 Nm3·h−1) vacuum pressure swing adsorption (VPSA) air separation system was established in Qinghai Province (in China) with an altitude of 3800 m, which was used to supply oxygen for relieving the hypoxia. The effects of adsorption and desorption time, purge and pressure equalization step and feed temperature on the performance of the process were investigated by performing experiments under plateau special conditions. Results showed that pressure equalization and intermittent purge steps could effectively improve the performance of the VPSA process. The system could produce 270 Nm3·h−1 of 90% O2 with 62.6% oxygen recovery from compressed air. The maximum productivity and minimum energy consumption with pressure ratio of 160:42 for ~90% O2 were 121.7 L·h−1·kg−1 and 0.55 kWh·Nm−3, respectively.

Enhancing biological signals and detection rates in single-cell RNA-seq experiments with cDNA library equalization.

Considerable effort has been devoted to refining experimental protocols to reduce levels of technical variability and artifacts in single-cell RNA-sequencing data (scRNA-seq). We here present evidence that equalizing the concentration of cDNA libraries prior to pooling, a step not consistently performed in single-cell experiments, improves gene detection rates, enhances biological signals, and reduces technical artifacts in scRNA-seq data. To evaluate the effect of equalization on various protocols, we developed Scaffold, a simulation framework that models each step of an scRNA-seq experiment. Numerical experiments demonstrate that equalization reduces variation in sequencing depth and gene-specific expression variability. We then performed a set of experiments in vitro with and without the equalization step and found that equalization increases the number of genes that are detected in every cell by 17–31%, improves discovery of biologically relevant genes, and reduces nuisance signals associated with cell cycle. Further support is provided in an analysis of publicly available data.

A Deep Learning Pipeline for Grade Groups Classification Using Digitized Prostate Biopsy Specimens.

Prostate cancer is a significant cause of morbidity and mortality in the USA. In this paper, we develop a computer-aided diagnostic (CAD) system for automated grade groups (GG) classification using digitized prostate biopsy specimens (PBSs). Our CAD system aims to firstly classify the Gleason pattern (GP), and then identifies the Gleason score (GS) and GG. The GP classification pipeline is based on a pyramidal deep learning system that utilizes three convolution neural networks (CNN) to produce both patch- and pixel-wise classifications. The analysis starts with sequential preprocessing steps that include a histogram equalization step to adjust intensity values, followed by a PBSs’ edge enhancement. The digitized PBSs are then divided into overlapping patches with the three sizes: 100 × 100 (), 150 × 150 (), and 200 × 200 (), pixels, and 75% overlap. Those three sizes of patches represent the three pyramidal levels. This pyramidal technique allows us to extract rich information, such as that the larger patches give more global information, while the small patches provide local details. After that, the patch-wise technique assigns each overlapped patch a label as GP categories (1 to 5). Then, the majority voting is the core approach for getting the pixel-wise classification that is used to get a single label for each overlapped pixel. The results after applying those techniques are three images of the same size as the original, and each pixel has a single label. We utilized the majority voting technique again on those three images to obtain only one. The proposed framework is trained, validated, and tested on 608 whole slide images (WSIs) of the digitized PBSs. The overall diagnostic accuracy is evaluated using several metrics: precision, recall, F1-score, accuracy, macro-averaged, and weighted-averaged. The () has the best accuracy results for patch classification among the three CNNs, and its classification accuracy is 0.76. The macro-averaged and weighted-average metrics are found to be around 0.70–0.77. For GG, our CAD results are about 80% for precision, and between 60% to 80% for recall and F1-score, respectively. Also, it is around 94% for accuracy and NPV. To highlight our CAD systems’ results, we used the standard ResNet50 and VGG-16 to compare our CNN’s patch-wise classification results. As well, we compared the GG’s results with that of the previous work.

Equilibrium Theory Analysis of Pressure Equalization Steps in Pressure Swing Adsorption

A binary, linear isotherm, isothermal equilibrium theory analysis of Skarstrom-type PSA cycles with bed-to-bed (BB) and bed-to-tank-to-bed (BTB) equalization steps was carried out with a binary gas mixture of A and B, with A more strongly adsorbed than B. For tractability, it was assumed that the gas produced from the light end of a bed contained only B and thus the recovery of A in the heavy product was 100%. Analytic expressions for the periodic state PSA cycle performances based on the recovery of B in the light product ReLP,B, the purity of A in the heavy product y̅HP, and the final pressures of the BB and BTB equalization steps were derived. The effects of the relative size of the equalization tanks Ψ (varied from 0.1 to 500) and the number of equalization steps n (varied from 1 to 10) were studied. The initial pressure in the bed at the beginning of the countercurrent depressurization (CnD) step ΠCnD,o was important. With increasing Ψ or n, ΠCnD,o always decreased and both y̅HP and ReLP,B always increased, and when the BTB and BB configurations achieved the same ΠCnD,o, their PSA cycle performances were identical. Increasing Ψ at constant n caused the BTB ΠCnD,o to approach that of the BB ΠCnD,o, and they became equal for only very large tanks (e.g., Ψ = 500). However, increasing nBTB at constant nBB and Ψ caused the BTB ΠCnD,o to be even lower than the BB ΠCnD,o for some reasonable Ψ. Therefore, instead of using larger tanks in BTB to achieve the same BB performance, it was better to increase nBTB at a reasonable Ψ to keep the tank volume smaller. For the same performance (i.e., the same ΠCnD,o), the total volume of all tanks (i.e., nΨ) decreased with increasing n, and in the limit of nBTB → ∞, nΨ approached a minimum total tank volume equal to nBB. This result indicated a lower limit exists on the minimum total volume of tanks required to achieve the same performance as in the BB configuration.

Design of an industrial multi-bed (V)PSA unit for argon concentration

Pressure swing adsorption systems have been devised to concentrate argon from a binary gas mixture of oxygen and argon (O2:Ar = 95:5 mol%) that an industrial oxygen generation vacuum swing adsorption (VSA) unit produces from air. The kinetically-driven adsorption processes investigated in this study contain a self-purging step and up to two double-ended pressure equalization steps. Three adsorption cycle configurations, each of which has one, two and three beds, were simulated. The effects of pressure ranges of the adsorption cycle, either pressure swing adsorption (PSA, 1–3 bar) or vacuum swing adsorption (VSA, 0.1–1 bar), as well as adsorption step time were extensively assessed with respect to the following separation key performance indicators (KPIs): argon purity, argon recovery, bed productivity and specific energy consumption. It turned out that argon purity and recovery could be significantly improved in the VSA cycles at the expense of bed productivity and energy consumption. The single VSA unit could not concentrate argon up to a purity of 98+% which is typically required for certain applications such as steel production and inert gas welding. Thus, a second VSA unit was added to increase further the argon purity and it was found that the integrated two-stage VSA system is capable of achieving the following overall performances: argon purity of 98.1%, argon recovery of 20.3%, bed productivity of 0.011 molAr kgads−1h−1 and specific energy consumption of 53.2 MJ kgAr−1. Considering real efficiencies of turbomachinery the energy consumption of the proposed VSA unit resulted 75% higher than that of a conventional stand-alone cryogenic distillation system designed to achieve the same separation. However, the VSA technology is expected to be a more attractive option than the cryogenic process in terms of CAPEX.

Optimization of pressure swing adsorption for hydrogen purification based on Box-Behnken design method

Pressure swing adsorption (PSA) is an important technology for mixture gas separation and purification. In this work, a dynamic model for a layered adsorption bed packed with activated carbon and zeolite 5A was developed and validated to study the PSA process. The model was validated by calculating breakthrough curves of a five-component gas mixture (H2/CH4/CO/N2/CO2 = 56.4/26.6/8.4/5.5/3.1 mol%) and comparing the results with available experimental data. The purification performance of six-step layered bed PSA cycle was studied using the model. In order to optimize the cycle, the Box-Behnken design (BBD) method was used, as implemented in Design Expert™. The parametric study showed that, for adsorption step durations ranging from 160 to 200 s, as the adsorption time increased, the purity decreased, whereas the recovery and productivity increased. During the pressure equalization step, the purity increased as the pressure equalization time increased, but the recovery and productivity decreased for step durations ranging from 10 to 30 s. As the P/F ratio (hydrogen used in purge step to hydrogen fed in adsorption step) increased from 0.05 to 0.125, the purity increased, whereas the recovery and productivity decreased. The optimization of the layered bed PSA process by the BBD method was then performed. In addition to the adsorption time, the pressure equalization time and the P/F ratio were considered as independent optimization parameters. Quadratic regression equations were then obtained for three responses of the system, namely purity, recovery, and productivity. When purity is set as the main performance indicator, the following values were obtained for the optimization parameters: an adsorption time of 168 s, a pressure equalization time of 14 s, and a P/F ratio of 0.11. Under those conditions, the system achieved a purity of 99.99%, a recovery of 57.76%, and a productivity of 6.41 mol/(kg·h).

Parallel and series multi-bed pressure swing adsorption processes for H2 recovery from a lean hydrogen mixture

The demand for clean energy sources has made H2 recovery from various lean hydrogen mixtures increasingly attractive. In this study, parallel and series pressure swing adsorption (PSA) processes were investigated experimentally and theoretically, and > 99% pure H2 was produced from a lean hydrogen mixture (H2:CO:N2:CO2 = 19.9:0.1:44.6:35.4 mol%) at 10 bar. A mathematical model for a PSA process using activated carbon and zeolite 13X was simultaneously validated with results from breakthrough experiments and a parallel two-bed PSA process. The parallel two-bed PSA process using a layered bed (lower bed: activated carbon, upper bed: zeolite 13X) experimentally produced H2 with a purity of 94.6–98.3% and a recovery of 33.5–63.2%; CO was not detected in the H2 product. In the parallel four-bed PSA process, the H2 recovery was drastically increased to 77.3% due to an additional pressure equalization step, but the increase in H2 purity was minute. The series PSA process, which was divided into the bulk separator and the purifier, was theoretically studied under various operating conditions. The series three- and four-bed PSA processes could produce H2 with over > 99% purity and a recovery of 62.478% and 82.643%, respectively, due to the additional pressure equalization step and the utilization of blowdown gas. The parallel four-bed PSA process showed the highest H2 productivity (33.58 molH2 kgads−1 day−1), while the series four-bed PSA process achieved an H2 productivity of 23.96 molH2 kgads−1 day−1 with > 99% H2 purity.

Enrichment of low grade CH4 from N2/CH4 mixtures using vacuum swing adsorption with activated carbon

Methane (CH4) is a cleaner fuel resource with relatively low carbon emissions and negligible particulate matters, heavy metals, and sulphur oxides, compared with those emission intensive fuels like coal. However, large amounts of CH4 emitted to the atmosphere drive significant greenhouse gas (GHG) effects due to the low value of its low concentration sources and technical difficulty of CH4/N2 separation. Therefore, it becomes crucial to advance the technology for separating low concentration CH4 from N2. In this study, a commercial activated carbon was used to separate CH4 from N2 with a 4-column vacuum swing adsorption (VSA) facility. Both light and heavy streams were firstly collected and stored in gas tanks, and then used for light/heavy purge. Four process modes involving A) 2-column and 8 steps, B) 3-column and 9 steps, C) 4-column and 16 steps, and D) 4-column and 20 steps were employed to investigate the effects of process design factors on their separation performance. Results showed that both pressure equalization and heavy product purge steps have significant impacts on product purity, recovery and productivity. In the case of 11.7 and 17.0% (CH4) feed gases, the methane products reached a purity around/above 30% and these gases can be compressed and transported for industrial utilization. Furthermore, the recovery of these low concentration methane gases will bring extra incentives with GHG mitigation benefits.

Biomethane production by adsorption technology: new cycle development, adsorbent selection and process optimization

Gas separation by adsorption processes such as pressure swing adsorption (PSA) presents an attractive alternative for upgrading biogas to biomethane. A new vacuum pressure swing adsorption (VPSA) cycle is proposed for a unit designed to purify pre-cleaned biogas (40% CO2 and 60% CH4) in industrial conditions (feed flow rate more than 500 Nm3/h and large-volume equipment). The process simulations performed to optimize the VPSA unit consider the kinetic separation of the feed components by using an appropriate carbon molecular sieve (CMS) adsorbent having a high kinetic separation selectivity for CO2 with respect to CH4. The designed VPSA unit is composed of five columns that perform three equalization steps. Minimizing methane losses during the regeneration steps necessitates injecting part of the off-gas rich in CO2 at the bottom of the column during the production step to push the CH4 forward. The produced biomethane meets the specification (97% CH4) of grid injection purity. The developed cycle allows a CH4 recovery of 92% to be obtained with a specific energy consumption of 0.35 kWh/Nm3, thus meeting the initial requirements for industrial exploitation of VPSA technology for biomethane purification from biogas sources.

Conceptual design of adsorptive recovery of ethane from residue gas stream using Na-ETS-10

This work provides the conceptual design of a pressure/vacuum swing adsorption cycle for recovering ethane from the residue gas stream (a mostly methane stream) using Na-ETS-10 as the adsorbent. The conceptual design for treating a stream with 2.4% ethane (and the rest methane) evolved from a simple 4-step cycle to more complex configurations which were able to simultaneously improve the ethane purity and recovery. Feed temperature played a key role in the cycle performance in terms of purity and recovery. The minimization of the recompression work of the light product (methane) was achieved by proposing a cycle design which includes a heavy reflux step at high pressure and a further pressure equalization step. Purity values up to 88% ethane with recoveries of 95% and productivities higher than 0.4 mol ethane/m3(ads)s were quantified through the optimization of the operating conditions for the reduced energy-cost adsorption cycle suggesting an alternative for ethane recovery in gas processing plants.

Inequality, Economic Growth, and Redistribution; Literature Review

Economists have long believed that economic growth will solve the problem of inequality and poverty. For decades, the question of whether and how inequality affects growth has been the subject of open debate in the academic world. In the same section, the redistribution which is considered part of the equalization step also has positive and negative impacts on economic growth. This paper presents a literature review consisting of several sections including: 1) literature review on the relationship between inequality and growth; 2) the relationship between redistribution and growth; 3) even distribution of infrastructure is part of the form of redistribution.

A parametric study of process design and cycle configurations for pre-combustion PSA applied to NGCC power plants

Natural gas combined cycle (NGCC) power plants show favourable conditions for the implementation of pressure swing adsorption (PSA) for the capture of carbon dioxide. These plants also show the advantage of a hydrogen co-production system. The challenge when implementing PSA in these plants is to achieve reference configurations that can obtain both products (hydrogen and carbon dioxide) at high purity levels, maximizing the recovery of hydrogen as a valuable product. This study presents the scale-up of a previously reported laboratory-based, four-bed, seven-step PSA model and a parametric study of the scaled-up PSA variables to maximize the product performance parameters. The capacity of the PSA model is based on the flow rate requirements of a GE-10 gas turbine, which can operate with up to 95% hydrogen purity. A parametric study using global system analysis (GSA) showed the effect of the bed diameter, length-to-diameter ratio and purge-to-feed flow rate ratio upon the product performance parameters. A purity of carbon dioxide of 95.37% and a hydrogen recovery of 92.27% was obtained with a purge-to-feed flow rate ratio of 0.22. The purity of hydrogen stayed close to 99.99%, with maximum deviations around 0.0001% for all case studies. The purity of the carbon dioxide and the recovery of hydrogen were further improved by considering additional PSA configurations. The addition of an assisted purge step and three pressure equalization steps improved these performance parameters by two percentage points. Overall, the model with one pressure equalization step, assisted purge step and rinse step after the feed step showed promising results with a purity of carbon dioxide of 98.28% and hydrogen recovery of 95.48%. Lower capitals costs are expected for this configuration, compared to adding pressure equalization steps using more than four fixed-bed units.

An unsupervised approach to improve contrast and segmentation of blood vessels in retinal images using CLAHE, 2D Gabor wavelet, and morphological operations

Retinopathies are the leading cause of eyesight loss, especially among diabetics. Due to the low contrast of blood vessels in fundus images, the visual inspection is a challenging job even for specialists. In this context, this work aims to implement image processing techniques to support contrast enhancement and segmentation of retinal blood vessels. The initial proposal consisted only of green channel separation, contrast limited adaptive histogram equalization, and 2D Gabor wavelet and mathematical morphology. The new proposal includes the edge and mask detection and the vessel enhancement 2D to preserve image’s characteristics. The development and validation of this work, in MatLab® environment, involved 40 images from Digital Retinal Images for Vessel Extraction (DRIVE), 20 images from Structured Analysis of the Retina (STARE), and 45 images from High-Resolution Fundus (HRF) database. In the unsupervised method context, the proposal presented the best performance regarding sensitivity and second place for balanced-accuracy on all databases. A subjective validation involving eleven ophthalmology professionals showed higher levels of acceptance (above 80%) after contrast limited adaptive histogram equalization (CLAHE) and vessel enhancement 2D steps and 75.5% for overall quality system. The main contributions refer to the inclusion of techniques for automatic mask detection, image edge removal, and suppression of vessels background to improve the retinal vessels segmentation process. In addition, this work made a computational interface named “Retinal Lab - A Tool for Fundus Image Analysis” available, which permits the users to adjust the contrast and segmentation of blood vessels in retinal images.

Cycle design and optimization of pressure swing adsorption cycles for pre-combustion CO2 capture

Novel pressure-swing adsorption (PSA) cycles were developed based on patented TDA AMS-19 (activated carbon) adsorbent for pre-combustion CO2 capture in integrated gasification combined cycle (IGCC) power plants. A variety of cycles comprising of counter-current blowdown, pressure equalization, steam purge and light product pressurization steps were designed and simulated using an in-house one dimensional detailed model. Full process optimization studies were performed for all cycles to evaluate their feasibility for pre-combustion CO2 capture. The CO2 purity and recovery Pareto fronts obtained using the multi-objective optimization were used to assess their ability to simultaneously achieve high CO2 purity (>95%) and recovery (>90%). The cycles that achieved the purity-recovery (95–90%) requirements were subjected to energy-productivity optimizations under the constraints of CO2 purity and recovery. Three cycle designs were ranked in terms of lowest energy consumption at 95% CO2 purities and 90% CO2 recoveries. It was found that a 10-step cycle with three pressure equalization steps achieved a minimum energy consumption of 95.7 kWhe/tonne of CO2 captured at a productivity of 3.3 mol CO2 captured/m3 adsorbent/s.

A numerical Study of Single Column Adsorber for Optimal Design of Pressure Swing Adsorption

Four different configurations of pressure swing adsorption (PSA) were designed numerically using Matlab software. The PSA system was applied to separate oxygen from air. The software was used first to validate previous experimental results of single bed adsorber. The results showed that the breakthrough time with product pressurizing is about 1000 s and mass transfer zone (MTZ) is steeper, while with the air pressurizing happened within 60s and MTZ was very wide. High purity of oxygen (>90%) was observed with the first and fourth configuration. Purity of about 88% was achieved with the third configuration, and low purity (75%) with the second configuration. In addition, high power consumption was indicated by the first, and second configurations. However, the third and fourth configurations consumed low power due to the pressure equalization step. Based on the results, the more economic and effective design is the fourth configuration.

Improved method to converge pressure equalization steps when simulating a cyclic adsorption process

Two new techniques for single-vessel Pressure or Vacuum Swing Adsorption (P-VSA) mathematical models are presented that improve convergence stability to Cyclic Steady State (CSS) when Pressure Equalization (PE) steps are involved.The first method, the Reflected Equalization Pressure (REP) method uses simplifying assumptions to derive a simple and efficient analytical solution for the unknown pressure profile boundary condition (BC) to use during PE steps on the first simulated cycle of a P-VSA simulation without the need for user-defined functions or additional ODEs.The second method, the Weighted Store-and-Retrieve (WSR) method is a variation on the Traditional Store-and-Retrieve (TSR) method for simulating PE steps where gases flow from one vessel to another in a single-vessel mathematical model. The WSR method retains history across several cycles, passing this back into the mathematical model via weighting factors to average the data and dampen the oscillatory response of a mathematical model to PE steps.Several examples of this technique are applied to the O2 VSA and H2 PSA systems.

Evaluation of simplified pressure swing adsorption cycles for bio-methane production

Pressure swing adsorption (PSA) is a mature technique for biogas upgrading. However, it constitutes the most expensive step to obtain fuel-quality bio-methane, particularly in small-scale units. To reduce the cost of upgrading in small-scale plants, we have evaluated different PSA cycles with two and three columns (less than commercial units). An equalization tank was used to perform one asynchronous pressure equalization step and keep the process fed continuous even in the case of using two columns. The effect of the purge step was also evaluated. Carbon molecular sieve was used as adsorbent. The feed composition was 40% CO2/60% CH4 and pressure swinging between 5 and 0.1 bar in the adsorption and blowdown steps, respectively. Four performance indicators (methane purity and recovery, productivity and energy consumption) were used to evaluate the PSA cycles. The mathematical model could predict the experimental PSA performance. Bio-methane with purity higher than 97.5% (specification) and recovery higher than 90% was obtained experimentally using a PSA with two columns and an equalization tank. When a third column is used (implementing an additional pressure equalization), the recovery increases in approx. 4% showing the importance of pressure equalization to reduce the methane slip.

A Pixon-based Image Segmentation Method Considering Textural Characteristics of Image

Image segmentation is an essential and critical process in image processing and pattern recognition. In this paper we proposed a textured-based method to segment an input image into regions. In our method an entropy-based textured map of image is extracted, followed by an histogram equalization step to discriminate different regions. Then with the aim of eliminating unnecessary details and achieving more robustness against unwanted noises, a low-pass filtering technique is successfully used to smooth the image. As the next step, the appropriate pixons are extracted and delivered to a fuzzy c-mean clustering stage to obtain the final image segments. The results of applying the proposed method on several different images indicate its better performance in image segmentation compared to the other methods.