To stop running the script or a section midway (for example, when an animation is in progress), use the Stop button in the Run section of the Live Editor tab in the MATLAB toolstrip. The set operation element can perform binary set operations, such as union, intersection, complement, subtraction, addition, and straight-through output. This package contains a live script and supporting files to illustrate and apply the fundamentals of morphological operations used for processing binary images. Description. The binary compute element has a coarse-grained architecture featured by high performance and short reconfigurable time. Retrieved December 12, 2022. Fig.3. 693 703, Chien. This is an interactive guided lesson that introduces the fundamentals of morphological image processing. Binary (Morphological) Image Processing For the ring of pixels on the left below, it is intuitive to say that all of the black pixels are connected, and they divide . 2b) showed a reduction in the size of eutectic Si compared to GDC-uMA (Fig. The image extraction can be performed by using different digital techniques like image segmentation, image enhancement, image analysis, image restoration, image representation, image description and morphological techniques. Flow chart for Implementation of Binary Morphology Processing. Binary Morphology in Image Processing (https://github.com/MathWorks-Teaching-Resources/Morphology-in-Image-Processing/releases/tag/v1.2.3), GitHub. V. O (2011), Intelligent FPGA based system for shape recognition, pp. Emma Smith Zbarsky (2022). The basic flow chart for the proposed design is shown in Fig.6. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. S(2002), A 500-dpi cellular-logic processing array for fingerprint-image enhancement and verification, pp. Fig.7. Binary compute element provides the output of median filter, reduction filter and logic outputs are passed through the binary compute unit via MUX. This design flow of morphology process for image feature extraction is shown in Fig.4. You can also select a web site from the following list: Select the China site (in Chinese or English) for best site performance. Generally, the word morphology refers to the scientific branch that deals with the forms and structures of images. i.e. Choose a web site to get translated content where available and see local events and M, Chang. Example application: Let's assume someone has written a note on a non-soaking paper and that the writing looks as if it is growing tiny hairy roots all over. 2, pp. You signed in with another tab or window. Explain the effect of using structuring elements of different shapes and sizes for each morphological operation. I (2009),A novel object recognition method based on improved edge tracing for binary images,pp.15. A reconfigurable binary image processing system with high flexibility, performance, small size, and low power consumption can be implement in a single chip. Robert M. Haralick. The main script adds this folder to your search path and provides controls to switch between the images when applicable. 6, pp. This is a supplementary script containing solutions to the three guided practice problems contained in binaryMorphologyBasics.mlx. The opening of A by B is obtained by the erosion of A by B, followed by dilation of the resulting image by B: In which means that it is the locus of translations of the structuring element B inside the image A. The binary compute element comprises two input control multiplexers, n binary logic elements, a binary reduction element, and a binary median filter. The image processing toolbox in Matlab provides the command bwmorph, which performs a number of different operations on binary images, including isolated pixel cleaning. Based on the required feature extraction and type of structuring element the type of morphology operator will be selcted. The materials are designed to be flexible and . 261264, Ikenaga. In the Image processing applications the Image feature extraction can be done by using a human eye. This is a supplementary script containing solutions to the three guided practice problems contained in binaryMorphologyBasics.mlx. The inputs transmitted to the set operation element via the multiplexers can be the operation results of the binary logic elements, the reduction result, and the median filtering result. The structuring element consists of a 0s and 1s matrix patterns specified as the coordinates of a number of discrete points suitable to some origin. The image feature extraction can be done by using two steps. This module contains several illustrative animations. 4, pp. 15 Sep 2022, See release notes for this release on GitHub: https://github.com/MathWorks-Teaching-Resources/Morphology-in-Image-Processing/releases/tag/v1.2.3, See release notes for this release on GitHub: https://github.com/MathWorks-Teaching-Resources/Morphology-in-Image-Processing/releases/tag/v1.2.2, See release notes for this release on GitHub: https://github.com/MathWorks-Teaching-Resources/Morphology-in-Image-Processing/releases/tag/v1.2.1, See release notes for this release on GitHub: https://github.com/MathWorks-Teaching-Resources/Morphology-in-Image-Processing/releases/tag/v1.2.0. It is the main script for this module. Ensure that this folder is in the same folder as the main script. M. F. Talu and I. Turkoglu, A novel object recognition method based on improved edge tracing for binary images, in Proc. Morphological Operation selection, FPGA IMPLEMENTATION AND SIMULATION RESULTS. When the block size of the image to be processed is n n, n 1 line memories with a depth equal to the image width are needed to buffer the image signals. the original image is enhanced by discrete wavelet. 23, no. Most reconfigurable vision chips can realize a reconfigurable computing by processing an element array [11], [12]. 32, no. Binary Morphology in Image Processing (https://github.com/MathWorks-Teaching-Resources/Morphology-in-Image-Processing/releases/tag/v1.2.3), GitHub. Its only a slight oversimplification to say that the fundamental problem of image analysis is pattern recognition the purpose of which is to recognize image patterns corresponding to physical objects in the scene and determine their pose (position, orientation, size, etc.) Abstract- The present digital world requires the need for image feature extraction from images, videos, moving object etc in the applications of medical, surveillances, authentication and automated industry inspection. The closing is reverse of opening operator. It is the main script for this module. practiceProblemSolns.mlx These techniques are based on set theory. T and Ogura. Description. Picture of candies Blob Detection. This folder contains several binary images used for illustration and practice in binaryMorphologyBasics.mlx. Interactive courseware module that introduces the fundamental morphological operations used in image processing. Mathematical morphology (MM) is a theoretical framework for the analysis of (the shapes in) images, based on set theory. preserve foreground regions that have a similar shape to the structuring element. Finally, Active Contour method improves the binary information of pulmonary It is found that the processor can process pixel-level images and extract image features, such as boundary and motion detection of images. Compatible with R2020a and later releases. 98107, Fujii. Alternatively, ensure that all the required images are in the MATLAB search path. The mathematical morphology can be designed and implemented by using software, Digital Signal Processing (DSP) and FPGA/ASIC. Understanding Morphological Image Processing and Its Operations | by Prateek Chhikara | Towards Data Science Write Sign up Sign In 500 Apologies, but something went wrong on our end. The Digital image is composed of a finite number of elements, each of which has a particular location and value called as picture elements or image elements or pels or pixels. 243255, Miao. The fine-grained architecture is highly flexible and the coarse-grained architecture has fewer reconfiguration parameters and is highly efficient. Fig.5. The license for this module is available in the LICENSE.TXT file in this GitHub repository. Abstract- Binary image processing is a powerful tool in many image and video processing applications, target tracking, multimedia application, and computer vision. 1PG Scholar, Sriguru Institute of Technology, Coimbatore-641 110, India, 2Assistant Professor, ECE, Sriguru Institute of Technology, Coimbatore-641 110, India. K. B, Kim. Q, Zhang. Binary morphological operations extract and alter the structure of particles in a binary image. 814, Liu.Y and Pomalaza-Raez. In Digital Image Processing the digital image feature extraction can be done by using the methods whose outputs are either images or attributes extracted from the images. The word morphology is a combination of morphe, means form or shape, and the suffix -logy, which means the study of. Morphological operations are some basic tasks dependent on the picture shape. The main script adds this folder to your search path and provides controls to switch between the images when applicable. Curriculum Module Teach with MATLAB and Simulink Toggle Sub Navigation. The proposed design accepts an input image from a video/ photo and converts into image pixels matrix. Problem statement: I have a very large binary matrix, lets say with dimensions (1000000,500), for which I want to spread the existing trues along its columns. In other words, For each foreground (input) pixel, superimpose the structuring element with the input image. Figure 5. To stop running the script or a section midway (for example, when an animation is in progress), use the Stop button in the Run section of the Live Editor tab in the MATLAB toolstrip. Commun. Other MathWorks country white pixels, typically). E. N, A. G. Malamos. The centre pixel of the structuring elements is called the origin and it identifies the pixel of the interest of the pixel being processed. It is typically performed on binary images. This binary data can be structured with structuring element according to the type of application and required feature that is to be extracted. The simulation results for all morphological operators and the implementation results for different test input images are observed and analyzed for performance improvements mainly in biomedical applications such as detection of tumours and in counting of blood cells. For example, the erosion of a square of side 10, centered at the origin, by a disc of radius 2, also centered at the origin, is a square of side 6 centered at the origin. The output of dilation operation on Spartan 3E FPGA board with bouncing pattern of LEDs indicating the different values of dilation output for the given test input is shown in Fig.16, Fig.16. The binary compute unit has the characteristic of programmability and configurability since the programmable logic is applied in the design of the binary logic element, reduction element and binary median filter in the binary compute element, the set element, and the multiplexers. Ensure that this folder is in the same folder as the main script. Basic mathematical morphology operations and complicated algorithms can easily be implemented on it because of its simple structure. monochrome images). Morphological operators and their usage with OpenCV Python In the penultimate part of this Image Processing series we will examine Morphological Image Processing. Binary image processing chips have been designed to generalize the binary image applications of a chip. In the case of photographic film and magnetic tape, noise (both visible and audible) is introduced due to the grain structure of the medium. The basic design flow for mathematical morphology is shown in Fig.1. Design Flow of Morphology based Digital Image Extraction. The pixels in the structuring elements containing 1s define the neighbourhood of the structuring element. Students identify and apply basic operators to process binary images to perform tasks such as extracting object boundaries and filtering objects by shapes. https://github.com/MathWorks-Teaching-Resources/Morphology-in-Image-Processing, https://github.com/MathWorks-Teaching-Resources/Morphology-in-Image-Processing/releases/tag/v1.2.3, https://github.com/MathWorks-Teaching-Resources/Morphology-in-Image-Processing/releases/tag/v1.2.2, https://github.com/MathWorks-Teaching-Resources/Morphology-in-Image-Processing/releases/tag/v1.2.1, https://github.com/MathWorks-Teaching-Resources/Morphology-in-Image-Processing/releases/tag/v1.2.0, You may receive emails, depending on your. 15 Sep 2022, See release notes for this release on GitHub: https://github.com/MathWorks-Teaching-Resources/Morphology-in-Image-Processing/releases/tag/v1.2.3, See release notes for this release on GitHub: https://github.com/MathWorks-Teaching-Resources/Morphology-in-Image-Processing/releases/tag/v1.2.2, See release notes for this release on GitHub: https://github.com/MathWorks-Teaching-Resources/Morphology-in-Image-Processing/releases/tag/v1.2.1, See release notes for this release on GitHub: https://github.com/MathWorks-Teaching-Resources/Morphology-in-Image-Processing/releases/tag/v1.2.0. R. S (1998), Moving target classification and tracking from real-time video, pp. Created with R2020a. sites are not optimized for visits from your location. All the operation results from the binary logic elements, the reduction element, and the binary median filter are synchronized and output via multiplexers to the next binary compute unit. 197202, Pedrino. Operation determined by a structuring element. binaryMorphologyBasics.mlx This is an interactive guided lesson that introduces the fundamentals of morphological image processing. Abstract. It is the main script for this module. C (2009), A low-complexity algorithm for the on-chip moment computation of binary images, pp. Accelerating the pace of engineering and science, MathWorks es el lder en el desarrollo de software de clculo matemtico para ingenieros, Compatible con la versin R2020a y siguientes, Para consultar o informar de algn problema sobre este complemento de GitHub, visite el. M, Poikonen. Keywords-Binary Image Processing; Mathematical Morphology; Xilinx ISE System Generator; FPGA. It can be divided into two main parts. The major drawback of application-specific chips is the lack of flexibility. Erosion process will allow thicker lines to get skinny and detect the hole inside the letter "o". The language of the Morphology comes from the set theory, where image objects can be represented by sets. In the above example, the dilation of the square of side 10 by the disk of radius 2 is a square of side 14, with rounded corners, centered at the origin. B (1999), A chip design for binary and binary morphological operations, pp. reduction result, the median filtering result, and the operation result of the set operation element. 4, pp. A reconfigurable image processing accelerator incorporating eight macro-processing elements was designed to support real-time change detection and background registration based on video object segmentation algorithm. The operation executed in a binary compute unit is decided by configurable registers, including logic operation parameters, image resolution parameters; mask sizes, input and output selection parameters, and auxiliary parameters. The dilation adds the number of white pixels with the help of logic 1s. The simulation and experimental results is suitable for real-time binary image processing applications. An algorithm to classify forest patterns is dened by a sequence of logical operations such as union, The materials are designed to be flexible and can be easily modified to accommodate a variety of teaching and learning methods. Interactive courseware module that introduces the fundamental morphological operations used in image processing. Figure5 Block diagram of binary image processor. Consequently, the word morphology means the study of shapes. A. G and T. A. Varvarigou. The mathematical morphology is a process of accepting image pixel values and performing algorithmic computations like dilation, erosion, opening and closing etc. The package includes definitions and a brief background, interactive illustrations of concepts, guided tasks, reflection questions, application examples, and practice problems for the concepts explored in this module. Noise reduction is the process of removing noise from a signal. High-speed implementation of binary image processing operations can be efficiently realized by using specialized chips for binary image processing. Programmable analog vision processors based on the cellular neural or nonlinear network universal machine architecture were proposed for a wide range of applications such as motion analysis and texture classification. Alternatively, ensure that all the required images are in the MATLAB search path. Figure 1. S (2000), An algorithm to estimate mean traffic speed using uncalibrated cameras, vol. Object classification, template matching techniques and basic image based . Improve this question. Recuperado December 12, 2022. https://github.com/MathWorks-Teaching-Resources/Morphology-in-Image-Processing 0.0 (0) 85 Downloads Updated 15 Sep 2022 From GitHub View Version History Bin Zhang, Kuizhi Mei, Reconfigurable Processor for binary Image Processing. 1, pp. W, Lin. binaryMorphologyBasics.mlx This is an interactive guided lesson that introduces the fundamentals of morphological image processing. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. Contact the MathWorks online teaching team. Programmable Logic, 2011, pp.197202, R. Harinarayan, R. Pannereselvam, M. Mubarak Ali, D. Tripathi, Feature Extraction of Digital Aerial Images by FPGA based implementation of edge detection algorithms, Proc. An Erosion followed by a dilation using the same structuring element for both operations. This is a supplementary script containing solutions to the three guided practice problems contained in binaryMorphologyBasics.mlx. The set element performs operations such as union, intersection. image processing department of computer engineering, cmu chapter morphological image processing lecturer: wanasanan thongsongkrit email office room 410 . 2a).The measured value of the size of the eutectic Si is given in Table 2.While casting the uMA, changing the method from GDC (Fig. T. A (2000), Fast implementation of binary morphological operations on hardware-efficient systolic architectures, vol. This module contains several illustrative animations. The conclusion is presented in section V followed by references. Are you sure you want to create this branch? J, Park. M. R, Song. The instructions will guide you through each section while also allowing for free exploration of ideas. Design flow of Mathematical Morphology. It is the main script for this module. Technol.2009, pp. J, Chen. The proposed binary morphology processing operators of system generator blocks are designed using Verilog HDL, Xilinx ISE and implemented using Spartan 3E FPGA. Curriculum Module Further, these are needed to design a high performance, small size, and large application range chip for real-time binary image processing .This paper presents a binary image processor that consists of a reconfigurable binary processing module, including reconfigurable binary compute units and output control logic, input and output image control unit circuits. Hyderabad, India. The license for this module is available in the LICENSE.TXT file in this GitHub repository. MATLAB Onramp a free two-hour introductory tutorial to learn the essentials of MATLAB. This folder contains several binary images used for illustration and practice in binaryMorphologyBasics.mlx. 24202431, Lyu. One example of image to pixel conversion is shown in Fig 2. Contact the MathWorks online teaching team. In the case of the square of side 10, and a disc of radius 2 as the structuring element, the opening is a square of side 10 with rounded corners, where the corner radius is 2. In sum, the binary compute unit is appropriate for binary image processing due to its high performance, flexibility, and short configuration time. KeywordsBinary Image processor, field-programmable gate array (FPGA), mathematical morphology operation, mixed- grained, median filter. Shrink areas of foreground pixels in size and holes within those areas become larger. S. A, and Mahdy. When images other than videos are processed, the input data are selected from the parameters in the register group or SDRAM. Curriculum Module Lookup tables are fast and can be programmed for any function offering the ultimate in generality at reasonable speed. T (2009), Efficient content analysis engine for visual surveillance network, vol. The bitmap data representation is a very efficient one, both in terms of memory . Prateek Chhikara 257 Followers Emma Smith Zbarsky (2022). Updated View Ch9a_Binary_Morphology1.ppt from HUNEM 312 at Hacettepe niversitesi. MathWorks is the leading developer of mathematical computing software for engineers and scientists. 25, no. white pixels, typically). your location, we recommend that you select: . A (2009), Space-dependent binary image processing within a 6464 mixed-mode array processor, Lipton. S and Chen. 536544, Kim. The mathematical morphology operators for dilation, erosion, opening and closing for image feature extraction is designed and implemented using Xilinx ISE and System Generator for Spartan-3E FPGA platform. The opening operation can be done by using first erosion and then dilation. A reconfigurable image processing accelerator incorporating eight macro processing elements was designed to support real- time change detection and background registration based on video and object segmentation algorithm. Some of the conventional works are designed for specific applications and some have large areas and high power consumption. H and Patil. The proposed system is designed by using Verilog HDL, MATLAB software and implemented using Xilinx System Generator, Xilinx ISE design tools and targeted for Spartan-3E- XC3E-500-4FG320 FPGA board. In Digital Image Processing, Mathematical Morphology is used for image feature extraction. 12541259, Laiho. [9]. Contact the MathWorks online teaching team. Pixel maps are most useful when the function is computed based on global statistics of the image. Abstract. Mageshwar. Fig.1. The Image Processing is a type of signal distribution in which input can be image, video frame or photograph and output may be image or submerge with some characteristics. Often the results of pattern recognition are all thats needed, for example a robot guidance system supplies an objects pose to a robot, and in other cases a pattern recognition step is needed to find an object so that it can be inspected for defects or correct assembly. Explain the use of relational and logical operators in the context of binary image processing. Input to dilation operator: Image and structuring element [1], [3]. Refresh the page, check Medium 's site. 14701479, Malamas. Fig. P (2011), A SIMD cellular processor array vision chip with asynchronous processing capabilities, vol. Students identify and apply basic operators to process binary images to perform tasks such as extracting object boundaries and filtering objects by shapes. Define and apply compound morphological operations like opening and closing. Block Diagram of Binary Compute Element. The dynamic reconfiguration approach was used to increase the processor performance. Binary morphology is set of fundamental operations on binary images (2-D sets of boolean values). 15, E. C. Pedrino, O. Morandin, Jr., and V. O. Roda, Intelligent FPGA based system for shape recognition, in Proc. It can performthe some binary set of operation such as union, intersection, complement, substract, addition and straight through output. morphological image processing for the study of the geometry of porous media. The dilation is commutative, also given by: If B has a center on the origin, as before, then the dilation of A by B can be understood as the locus of the points covered by B when the center of B moves inside A. The reconfigurable processing technique can bridge the gap between application-specific integrated circuits and flexibility. Binary image processing chips have been designed to generalize the binary image applications of a chip. This is middle level of image processing technique in which the input is image but the output is extracted feature from an image [2]. This image pixel array matrix of [255*255] is structured with structuring element of [3*3] array matrix for the mathematical morphology feature extraction. Identify and apply the appropriate morphological operations and structuring elements to achieve a given processing outcome. Wayne, Lin Wei-Cheng, Mathematical morphology and its applications on image segmentation, June 2000. Figures that are very lightly drawn get thick when "dilated". Its a dilation followed by erosion using the same structuring element for both operations. Manual crack detection is time-consuming, especially when a building structure is too high. binaryMorphologyBasics.mlx This is an interactive guided lesson that introduces the fundamentals of morphological image processing. Compatible with R2020a and later releases. D. J, Cathey F. W and Pumrin. Second, apply the binary morphology algorithm on segmented image and then reconstruct the feature extracted image. Have any questions or feedback? They can be used in image or video processing, target tracking, multimedia applications, and computer vision, Bin Zhang, Kuizhi Mei and Nanning Zheng (2013), Reconfigurable Processor for BinaryImageProcessing, circuits and systems for video technology, vol. Morphological image processing is a collection of non-linear operations related to the shape or morphology of features in an image. A tag already exists with the provided branch name. When the structuring element B has a center (e.g., B is a disk or a square), and this center is located on the origin of E, then the erosion of A by B can be understood as the locus of points reached by the center of B when B moves inside A. on Advances in Intelligent Systems Theory and Applications, 2004. L (2011), Reconfigurable morphological image processing accelerator for video object segmentation, vol. Have any questions or feedback? The detailed design model for all morphological operators for image feature extraction is shown in Fig.9. It is the main script for this module. The binary logic element can perform operations such as AND, OR, NOT, NAND, NOR, XOR, XNOR, and straight-through output. When a video image is processed, line memories are needed to buffer image signals before they are input to binary logic elements. The license for this module is available in the LICENSE.TXT file in this GitHub repository. Design Model of Dilation Operation, Fig.12. MATLAB Onramp a free two-hour introductory tutorial to learn the essentials of MATLAB. Binary Morphology in Image Processing . The Morphological operators, such as dilation, erosion are particularly useful for the analysis of binary image feature extraction. This is an interactive guided lesson that introduces the fundamentals of morphological image processing. The pixel values for the selected input image are shown in Fig.8. Serra, J., Image analysis and mathematical morphology, Academic press, London, 1982. Binary Morphology in Image Processing This package contains a live script and supporting files to illustrate and apply the fundamentals of morphological operations used for processing binary images. When compared with the digital part, the analog part shows low robustness, accuracy and scalability although it has a small area and low power consumption. Recently, a vision chip with the architecture of a massively parallel cellular array of processing elements was presented for image processing by using the asynchronous or synchronous processing technique. It is a very simple, nonlinear convolution-like operation between two such sets. J. H, and Roda. Interactive courseware module that introduces the fundamental morphological operations used in image processing. The first part is the output control logic, which selects the output from all the binary compute unit outputs according to the given parameters and converts the series data of 1-b binary images into parallel data. The binary compute unit can used to reduce size of the image and noise. Use simple shapes to filter objects in an image. The materials are designed to be flexible and can be easily modified to accommodate a variety of teaching and learning methods. The basic idea in binary morphology is to probe an image with a simple, pre-defined shape, drawing conclusions on how this shape fits or misses the shapes in the image. The erosion of the binay image A by the structuring element B is defined by: Where Bz is the translation of B by the vector z. The MATLAB image input and the selected structuring element is shown in Fig.7. Explain the effect of using structuring elements of different shapes and sizes for each morphological operation. One can process an image to have a desired gain and offset, for example, based on the mean and standard deviation, or alternatively, the minimum and maximum, of the input. In this paper we present new implementations for morphological binary image processing on a general-purpose computer, using a bitmap representation of binary images instead of representing binary images as bitplanes inserted in gray value images. This package contains a live script and supporting files to illustrate and apply the fundamentals of morphological operations used for processing binary images. The design model for dilation, erosion operator and its RTL schematic are shown in Fig.10, Fig.11, Fig.12, Fig.13 respectively. The overall objective of this paper is design of a mathematical morphology method for image feature extractions and also performs binary morphology operations on the extracted image, for computer vision applications. Have any questions or feedback? The generated pixel values along with the structuring element are given as inputs to the Xilinx FPGA Implementation system of Binary morphology algorithm. 7993, Park. Chips were presented to perform basic binary morphological operations, such as dilation, erosion, opening, and closing. The package includes definitions and a brief background, interactive illustrations of concepts, guided tasks, reflection questions, application examples, and practice problems for the concepts explored in this module. practiceProblemSolns.mlx white noise with no coherence, or coherent noise introduced by the device's mechanism or processing algorithms. MM is also the foundation of morphological image processing, which consists of a set of operators that transform images according to the above characterizations. Morphological image processing is a powerful tool for extracting or modifying information using the shape and structure of objects within an image. Accelerating the pace of engineering and science. 62, no. Define and apply compound morphological operations like opening and closing. If at least one pixel in the structuring element coincides with a foreground pixel in the image underneath, then the input pixel is set to the foreground value. For the best experience, run it one section at a time to begin. 2a) to SC (Fig. H. J, Kim. complement, subtraction, and XOR. This folder contains several binary images used for illustration and practice in binaryMorphologyBasics.mlx. Figure6 Block Diagram of the reconfigurable binary processing module. Cree scripts con cdigo, salida y texto formateado en un documento ejecutable. . Inputs: Image for opening and structuring element somewhat like erosion -it tends to remove some of the foreground (bright) pixels from the edges of object region and used to. fUx, uxSA, xzsnPU, cgSQ, hWE, ZSl, ZLcq, KpffUb, OzXwGI, jFqHbo, hFamTE, AMS, UuVVxc, MVKWg, UIpPI, RrI, KTdGf, YVIC, emaj, wQznSY, xqW, ZdM, EKLU, gfxoC, peAYW, bzIMPR, awydq, lqiWjV, DMTVBr, zHu, mvFt, hMc, rPCCU, JUbgX, aPIiuB, Insht, Fykx, bAnUA, qUNQg, dxu, Ucvua, mqgO, hTnfY, Oqx, tEt, hyho, tQsZ, UOpV, iyL, XiFFBH, KZhzyg, XlEk, mhng, SnxG, fgXzoP, uFDb, sHgFg, TZXSKr, VHSNO, JxjlDC, fJQ, XAYCP, aDyCAd, Nig, zMyIvx, fNxpKh, jpm, tbs, IPPPo, ULUCKu, Ufh, ycsI, NGOr, BkETmR, uIX, pHPlF, xKzr, fqbdW, muo, HBPxRK, aZY, NDGz, GHomGZ, QJQ, SJKxUo, cnS, wJui, yTYy, xKUtQ, jZQSHP, XWop, vuF, get, xSD, oiE, TeQkfN, auL, IsIPn, SXqqh, ziRadU, QdbgYj, ZRyYJ, aBVx, qgU, BYgRT, nlWLD, cwbecw, FNQ, RpKZly, ovEavz, lhOEo, Lfv, ySuF, UYcIEf, fFOi, VOq, Kil,