Monotonic sequences for image enhancement and segmentation

Grigoryan, Artyom M.; Agaian, Sos S.

doi:10.1016/j.dsp.2015.02.011

Cited by 14 publications

(3 citation statements)

References 50 publications

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“…The histogram is used for analysis. A better threshold is selected according to the relationship between the peaks and troughs of the histogram [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

An Improved Grey Wolf Optimizer Based on Differential Evolution and OTSU Algorithm

Liu

Sun

et al. 2020

Applied Sciences

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Aimed at solving the problems of poor stability and easily falling into the local optimal solution in the grey wolf optimizer (GWO) algorithm, an improved GWO algorithm based on the differential evolution (DE) algorithm and the OTSU algorithm is proposed (DE-OTSU-GWO). The multithreshold OTSU, Tsallis entropy, and DE algorithm are combined with the GWO algorithm. The multithreshold OTSU algorithm is used to calculate the fitness of the initial population. The population is updated using the GWO algorithm and the DE algorithm through the Tsallis entropy algorithm for crossover steps. Multithreshold OTSU calculates the fitness in the initial population and makes the initial stage basically stable. Tsallis entropy calculates the fitness quickly. The DE algorithm can solve the local optimal solution of GWO. The performance of the DE-OTSU-GWO algorithm was tested using a CEC2005 benchmark function (23 test functions). Compared with existing particle swarm optimizer (PSO) and GWO algorithms, the experimental results showed that the DE-OTSU-GWO algorithm is more stable and accurate in solving functions. In addition, compared with other algorithms, a convergence behavior analysis proved the high quality of the DE-OTSU-GWO algorithm. In the results of classical agricultural image recognition problems, compared with GWO, PSO, DE-GWO, and 2D-OTSU-FA, the DE-OTSU-GWO algorithm had accuracy in straw image recognition and is applicable to practical problems. The OTSU algorithm improves the accuracy of the overall algorithm while increasing the running time. After adding the DE algorithm, the time complexity will increase, but the solution time can be shortened. Compared with GWO, DE-GWO, PSO, and 2D-OTSU-FA, the DE-OTSU-GWO algorithm has better results in segmentation assessment.

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“…The histogram is used for analysis. A better threshold is selected according to the relationship between the peaks and troughs of the histogram [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

An Improved Grey Wolf Optimizer Based on Differential Evolution and OTSU Algorithm

Liu

Sun

et al. 2020

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…For positive numbers 𝑎 and 𝑏, this ratio equals to 𝛷 = 𝑏/𝑎 = (𝑏 + 𝑎)/𝑏, if 𝑏 > 𝑎. The number 𝛷 was found in proportions of parts in construction of Egyptian pyramids [3], in arts [4]- [6], in fashion [7], in medicine [8,9], face detection [10], image enhancement [11,12], and many applications in engineering.…”

Section: Introductionmentioning

confidence: 99%

On a Lexical Vector in Teaching English Grammar

Grigoryan¹,

Grigoryan²

2020

IvSU.H

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There exist quite a few methods of teaching English grammar. Probably, the most traditional and at the same time the most widely spread one is the so-called rule-based teaching of grammar. The method consists in students transferring the formally learnt rules to the real life practice. Our hands-on experience in teaching grammar proves that while the method works for some students, it definitely does not work for everybody. There are quite a number of students who find mastering grammar easier through creating close associations of certain grammatical constructions with certain lexical components.

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“…The first category includes studying better ways to weaken background information and highlight feature information. Grigoryan and Agaian [5] described a unified approach for signal thresholding by introducing the general concept of weighted thresholding using monotonic sequences for signal and image set-theoretical representation. The main advantage of this representation is that it allows for the performance of nonlinear operations by a weighted threshold, enhancing many geometric features present in the original signals and images via coefficient manipulation and weighting.…”

Section: Introductionmentioning

confidence: 99%

Improved Morphological Band-Pass Filtering Algorithm and Its Application in Circle Detection

Xian

Zhao

Tan

2018

Mathematical Problems in Engineering

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Existing image segmentation and image enhancement methods are deficient in complex industrial environments. Therefore, an improved morphological band-pass filter algorithm is presented. The first step of the algorithm is obtaining two marker images by erosion operations for a test image with two kinds of structuring elements: one slightly larger and one smaller than the feature but similar in shape. The second step is obtaining an image only, including the background, and an image including the feature with the background, excluding noise. The final step is realizing the feature segmentation by carrying out a difference operation on the two images. Selection of the structuring elements in the algorithm and the computational cost reduction are also discussed for engineering applications. Experimental results show that the proposed algorithm achieves the accurate segmentation of the circle at a specific scale through the velocity-optimized morphological operation and features good real-time performance and high accuracy in complex industrial environments, which could meet the requirements of industrial online monitoring.

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Monotonic sequences for image enhancement and segmentation

Cited by 14 publications

References 50 publications

An Improved Grey Wolf Optimizer Based on Differential Evolution and OTSU Algorithm

An Improved Grey Wolf Optimizer Based on Differential Evolution and OTSU Algorithm

On a Lexical Vector in Teaching English Grammar

Improved Morphological Band-Pass Filtering Algorithm and Its Application in Circle Detection

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