Danial Ahmadzadeh, Mohammad Fiuzy, Javad Haddadnia · 2013
Although the amount of stomach cancer has reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. In Iran , stomach cancer is one of the most common illness in some areas like northwest and northeast . In this study we aim to suggest a new way for diagnosing this illness. One of the main problems with this illness is that the diagnosis process doesn’t take place at the right time. Nowadays doctors try to diagnose this illness on the basis of their experiences, knowledge, and complicated surveys but all humans have error in their works. Data in this study are selected from 55 subjects (selected randomly). By using image processing and artificial intelligence algorithms like primary preprocessors for increasing the quality and statistical characteristics of image, local binary pattern algorithm for elicit characteristics, image histogram algorithm to elicit impaired characteristics and support vector machine has been used for accurate classification among impaired and suspected subjects and also for accurate diagnosis of impairment. The suggested system by using a combination of mentioned methods was succeed to achieve 91.8% accurate diagnosis. Although available methods are accurate but they are really expensive and time consuming, by comparing this method with those mentioned above are will have a better understanding of its accuracy and usefulness.
Cited by 16
Jianjian Dai, Haotian Xu, Yongxiang Gao et al. · Industrial & Engineering Chemistry Research · 2024
Rotating drum experiments on binary mixtures of plastic spheres with wood spheres, wood cylinders, plastic cylinders, and wood cubes were investigated, respectively. A high-resolution camera was employed to record the flow behaviors of the binary mixtures. A machine learning-assisted image processing method was developed to segment the particles of different shapes, and its superiority was demonstrated by comparing the results with the pixel and artificial counting methods. This method was used to analyze the images recorded from binary mixture experiments to explore the effects of rotating speed, particle shape, and density differences on mixtures’ radial and axial mixing and segregation behavior. The results show that the particle shape and density difference significantly affect the resolution angle of the binary mixture containing plastic spheres. In the radial direction, the degree of mixing of the binary mixtures containing wood spheres and cubes is not sensitive to speed. The degree of mixing of the binary mixture containing cylindrical particles increases linearly with the rotating speed within a specific range. The particle shape significantly affects the radial segregation of the binary mixtures. In contrast, the rotating speed has a negligible effect on the radial segregation of binary mixtures containing wood spheres, cylinders, and cubes.
Cited by 5
Frederick M. Waltz · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1995
A new method of implementing a wide range of standard image processing operations in a real-time finite-state-machine architecture has been presented at various conferences in the past year. This architecture, under the generic name SKIPSM (separated-kernel image processing using finite state machines), has been shown to be capable of carrying out binary morphology with very large arbitrary structuring elements, simultaneous application of many binary structuring elements, gray-level morphology, binary and gray-level template matching, binary skeletonization, binary correlation, row and column summations, and many other operations. This paper describes inexpensive hardware implementations of the SKIPSM architecture, including a daughter board compatible with commercially available pipelined image processing hardware.
Cited by 12
Ya.G. Skoriukova, T.B. Martyniuk, Svetoslav Markov et al. · Optoelectronic Information-Power Technologies · 2024
The possibility of creating new effective approaches and methods for the operation of visual systems of mobile works for the identification of tasks and objects of objects is due to the requirements of today. The work method is an analysis of the features of halftone image processing using the method of binary slices to identify a reference image in the field of the current image. The methods of analysis, abstraction and analogy were used as research methods. Separate articles offer an approach to complementing a reference halftone image on a current halftone image. To do this, we note the features of using the method of binary slices for processing a halftone image in combination with methods that allow you to destroy the reference binary image on the current binary image. The proposed approach includes a step of forming a set of binary slices of the halftone current image, a step of forming a set of binary slices of the halftone reference image, a step of matching the binary slices of the reference to the binary slices of the current image, a step of determining the location of each binary slice of the reference on the corresponding slice of the current image, and a step analysis of the obtained results and determination of the location of the halftone reference image on the halftone current image. A solution is proposed using a specific example. The practical value of the proposed approach is that a complex halftone image with a large number of brightness levels can be reduced to simple binary matrices, most of which are simply excluded from the processing process. At the same time, there remains a choice of the method of determining the binary slice of the standard on the field of the binary slice of the current image.
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Ahmad Raza Khan (4846549), Christopher D. Kroenke (658398), Ove Wiborg (493243) et al. · Figshare · 2018
<p>(a, d) Contrast enhanced image, (b, e) binary image of contrast enhanced image and (c, f) binary image of contrast enhanced image (green) with cell body mask (white and pink) using image processing tool in Matlab. The Cell body mask was subtracted from the contrast enhanced a binary image to calculate the axonal and dendritic fraction of the image.</p>
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Kung-Shiuh Huang · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1990
Image processing afid image analysis tasks have large (lata processing requirements and inherent parallelism. Because they involve a large amount of data, their operations can he extremely complex. During the past few years, numerous papers lave used an algebraic approach to aid in image processing [Serra82, Lotigheed8o, JUL Lcr87, Ciardina8i, Agui82, lluang87aJ. A simple algebraic system for expressing parallel image transformations would be very helpful for people to learn the art of parallel image processing, to compare different algorithms and architectures, arid to design a special-purpose image processor. Iii this paper, we use a binary image algebra (}31A) [ llnang89a, iluang9OJ, an axiomatic algebraic structure, to serve as a standar(l mathematical structure for the processing of binary images. Some parallel binary image processing architures can then be derived and compared. Section 2 reviews BEA and discusses the requirements for implementing A. Section 3 (liscusses three kinds of parallel architectures for f3JA: near-neighbor array architectures, hypercube architectures, and pipeline architectures. Section 4 discusses their implementation techniques. Section 5 gives a conclusion.
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John R. Jordan · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
Binary image processing techniques are often used to reduce the computational burden associated with image processing algorithms, thereby reducing costs and increasing throughput. When applicable, this approach is particularly useful for object detection, for which grey-level processing is quite slow. In this paper, a novel algorithm for detecting objects in binary images is presented. The fundamental advantage of this algorithm is the use of binary connectivity edge maps, which represent the edge data in the binary image by detecting eight-connected neighborhood bit (intensity) patterns. Appropriate use of these connectivity edge maps yields object detection which is faster and more robust than traditional methods (image subtraction, image correlation). The efficacy of this algorithm is demonstrated by applying it to the automatic detection and location of alignment marks for semiconductor wafer alignment and directly comparing its performance against those of traditional approaches (image subtraction, image correlation) in terms of accuracy, invariance to object rotation, and algorithm speed.
Cited by 1
Danijela Ristić–Durrant, Axel Gräser · 2008
Abstract. In this paper the novel idea of including feedback control at the image segmentation level to overcome the problems of traditional digital image processing is presented. The main idea behind this is that the introduced closed-loop drives the current quality of the binary-segmented image to the desired quality, in order to provide the reliable binary image input to the higher processing levels. The conditions that a measure of image quality should satisfy to be used as the controlled variable in a closed-loop are discussed. The two-dimensional entropy of segmented pixels is proposed as a novel measure of the quality of a binary-segmented image that can be used as the feedback variable in the closed-loop control of image segmentation. Besides the input-output selection, both the selection of control structure and feedback control design are considered. The emphasis is on the specific features of image processing that make closed-loop control in this technology different from conventional industrial control. The benefit of feedback control in image processing is illustrated by its successful application to two real-word applications: object recognition in service robotics and corner detection in industrial images for ship welding. Key words: feedback control in image processing, image segmentation, industrial and service robotics image processing applications 1.
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İrem Poyraz, Mevlüt Akçura · Türk Tarım ve Doğa Bilimleri Dergisi · 2025
Appearance is one of the important traits in seeds. Appearance-related features such as shape, size, and color are important parameters in distinguishing seeds from each other. Machine learning algorithms are used to distinguishing plant seed species for different purposes. In this study, four faba bean cultivars (Alexia, Alice, Jasmin, and Arabella) were used to distinguishing based on appearance measurements including shape and size features analyzed in pairs. Eleven machine learning algorithms (NB, MLP, SGD, SL, LMT, SMO, kNN, J48, Random Forest, Random Tree, REPTree) were used to assess binary classification performance utilizing red-green-blue (RGB) color channels through a image processing system. Among all pairs, faba bean seeds of the Alexia and Alice cultivars had the greatest classification accuracy of 90.5% using the Random Forest, and 87.5% with the MLP, SGD, and J48 models. The MLP model achieved the highest accuracy rate of 87% for the categorization of Alexia vs Arabella cultivars, followed by the J48 model with an accuracy rate of 84%. The Alice cultivar possesses the greatest values for area (83.80 mm²), perimeter (47.43 mm), width (9.28 mm), and length (12.50 mm). Wilks' lambda results indicated that the variations in external appearance of faba bean varieties are significant (p < 0.01). All of these results indicated that machine learning algorithms can effectively differentiate faba bean seeds based on their physical characteristics.
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Frederick M. Waltz · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1996
In a series of eleven previous papers a radically different method of implementing a wide range of neighborhood image processing operations has been presented, under the acronym SKIPSM (separated-kernel image processing using finite state machines). Simply by changing the contents of two lookup tables, one can use the same software code or the same hardware configuration can carry out a long list of operations, including binary morphology with multiple large structuring elements, multiple simultaneous steps of the grassfire transform, 'fuzzy' binary morphological operations, grey-level morphology, binary skeletonization, binary correlation, binary openings and closings in one pass, and certain global image processing operations. The execution time is very fast, and is totally independent of the size of the neighborhood or of the number of simultaneous operations being performed. This paper gives a detailed description of the steps for creating lookup tables for binary morphology.
Cited by 11
Poyraz, İrem, Akçura, Mevlüt · DergiPark (Istanbul University) · 2025
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Niladri B. Puhan, Anthony T. S. Ho · 2014
Abstract- In this paper, we propose a new perception based watermarking algorithm in binary document images for secure authentication purpose. Binary image watermarking with pixel flipping approach is a challenging problem, because flipping the black and white pixels in such simple images can bring noticeable visual distortion. A novel perceptual based model was proposed towards digital watermarking of binary images in [9]. The model estimates the distortion resulting from flipping of a pixel by finding the curvature-weighted distance difference (CWDD) measure between original and watermarked contour segments. In this paper, the reversible property of the CWDD measure is used towards designing a new authentication watermarking algorithm so that the possibility of any undetected modification to the watermarked image is removed. This algorithm embeds an authentication signature computed from the original image into itself after identifying an ordered set of low-distortion pixels. The same ordered set of pixels are correctly found in both the embedder and blind detector through the design of necessary conditions. The ability of the proposed authentication algorithm to detect any modification in the watermarked image is equivalent to the security of cryptographic authentication. The parity attack found in the previous block-wise data hiding methods in binary images is not possible in the proposed algorithm due to pixel-wise embedding of the authentication signature. Simulation results show the imperceptibility of the watermarking process and successful detection of content modifications.
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Harris Turk, C. J. Munno · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
High speed spatial light modulators are typically binary in operation, which complicates their use as spatial filter masks when large dynamic range filters are needed. Wavelet image transformations may be implemented by a series of spatial filtering operations, but these filters typically must satisfy minimum uncertainty-principle or other constraints. For these constraints to hold, the amplitudes of the filter masks must closely follow the amplitudes of the appropriate wavelet kernel masks and therefore simple use of binary spatial light modulator (SLM) filter masks is impossible. A bit-slice method is therefore presented which can circumvent the dynamic range limitations of typical SLMs when used in coherent optical processors. The method takes advantage of the parallelism and linearity of optical processing and only results in a (log<SUB>2</SUB>N)<SUP>2</SUP> increase in complexity for images with N gray levels. Computer modeled results are presented.
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Jun Tanida, Yoshiki Ichioka · Journal of the Optical Society of America A · 1985
The optical-logic-array processor (OLAP), using a lensless shadow-casting system, has been applied to execute optical digital image processing for binary objects. The OLAP is an optical digital processor based on techniques of image coding and optical correlation that can optically implement parallel logic gates. To demonstrate further potential of the OLAP, several processing methods for gray-level objects are presented. Experimental results indicate applicability of the OLAP for parallel optical digital image processing for both binary and gray-level objects.
Cited by 26
Teguh Budi Prasetyo, Hakam Muzakki, Rifky Maulana Yusron et al. · Journal of Physics Conference Series · 2025
Abstract This study discussed image processing used to imprecision of micro product blanking. Image processing has been developed to improve the precision in the inspection process. Image of specimen, operate image to grey scale, binary of the image, operational mathematic of the binary image, and wide of inaccurate were studied in this study. The image of the micro blanking product could be taken with a digital microscopy camera, the image could be processed to show inaccuracy, and image processing could be used to analysis and measure wide of imprecision. Specimen more the 40 tend to imprecision and specimen more than 60 were not precision. The represent that tool must be changed when forced aluminium plate to dies at 40.
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Dong, Chen-Xi, Duan, Zhao, Li, Renwei et al. · Figshare · 2023
Binary image processing and pore recognition
Cited by 1Open access
Dong, Chen-Xi, Duan, Zhao, Li, Renwei et al. · Figshare · 2023
Binary image processing and pore recognition
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Sayantani Karmakar, Supriya Karmakar, Supriya Karmakar et al. · International Journal of Electronics Letters · 2018
Information increases in a signal by using more value to represent the signal. Compared to binary logic, multivalued logic carries more information about a signal. An image can be represented more faithfully with quaternary logic compared to binary logic. Binary logic consists only two states, whereas quaternary logic consists of four states. But the increase in states in the quaternary logic decreases the noise margin. As a result, noise signal affects a quaternary image information more than a binary image. Proper filters are necessary to image restoration from multivalued logic image processing. Savitzky–Golay (SG) filter is used here to preserve the information due to multivalued logic image processing. Comparative study is performed in terms of peak signal-to-noise ratio and mean squared error. This paper shows the application of quaternary logic in combination of SG filter in image enhancement.
Cited by 4
John V. Kennedy, Jim Austin, Rick Pack et al. · 1995
This paper describes the C-NNAP machine, a MIMD implementation of an array of ADAM binary neural networks, primarily designed for image processing. C-NNAP comprises an array of VME cards each containing a DSP, SCSI controller and the SAT peripheral processor. The SAT processor is a dedicated hardware implementation that performs binary neural network computations. The SAT processor yields a speed-up of greater than 180 times over the current DSP with its dedicated coprocessor. C-NNAP in association with the SAT processor provide a fast, parallel environment for performing binary neural network operations. 1. Introduction Binary neural networks based on the N-tuple method [6] have been used in image processing for pig evisceration [1], scene analysis [5] and they also have potential for use in knowledge manipulation [3]. However, an obstacle to the use of binary neural networks in real-time image processing systems is the requirement to process large quantities of data. The binary neur...
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Ravindra A. Athale, Joseph N. Mait, Dennis W. Prather · 1991
Morphological image processing based on binary set representation of an image has been receiving increasing attention as a viable alternative to the linear image processing based on Fourier domain filtering [1], The fundamental morphological filtering operations of erosion and dilation are nonlinear operations from which more complex operations (opening, closing, pattern spectra) suitable for shape extraction and analysis can be synthesized. The morphological operations are defined between a working image and a much smaller image called the structuring element. In most cases the structuring element is binary while the working image can be binary, analog with binary threshold decomposition representation or analog with weighted binary representation. For the first two representations, the dilation and erosion operations consist of a superposition of several shifted replicas of the working image followed by a point-wise threshold operation at different levels; 1 for dilation and (m-1) for erosion, where "m" is the number of images superposed. With the third representation, the minimum/maximum value (for dilation/erosion, respectively) for the superposed pixels is detected and assigned as the pixel value in the output image. In either case, the processing operations are of low complexity. The number of shifted replicas of the working image and the amount of shift corresponds to the number and position, respectively, of bright pixels in the structuring element. For large and irregularly shaped structuring elements the morphological processing operation complexity is dominated by data communication.
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