Image texture surface analysis using an improved differential box counting based fractal dimension

Panigrahy, Chinmaya; Seal, Ayan; Mahato, Nihar Kumar

doi:10.1016/j.powtec.2020.01.053

Cited by 32 publications

(11 citation statements)

References 39 publications

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“…BCD is one of the common types of fractal dimension that can represent the fractal and geometrical properties of objects [23]. Moreover, the BCD has a significant advantage of being easily measured with unknown gradation [24].…”

Section: Box-counting Methods For Numerical Objectsmentioning

confidence: 99%

Fractal-Dimension-Based Walking Trajectory Analysis: A Case Study in Museum J. Armand Bombardier

Han

Zhan

2021

Advances in Civil Engineering

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A comprehensive understanding of the randomness, arbitrariness, and complexity of the visitors’ behavior and interaction in a museum is important because it is associated with the design. There is still uncertainty about how to characterize the visitors’ behavior and interaction. The fractal dimension was used in this study to indicate the geometrical form of the aged’s, the families’, and the students’ walking trajectories. The study results represented that all three sorts of the walking trajectory fractal-dimension-time curves fluctuated in the early stage. A remarkable exponential converges could then be observed. The mean fractal dimension after the convergence of the aged’s, the families’, and the students’ walking trajectory was nearly 1.8, 1.6, and 1.2, respectively. Furthermore, the behavior characteristics of these three sorts of visitors were quantified and the reasons were speculated and inferred. The comprehensive consideration of fractal geometry can aid in visitors’ behavior modeling and museum design.

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Section: Box-counting Methods For Numerical Objectsmentioning

confidence: 99%

Fractal-Dimension-Based Walking Trajectory Analysis: A Case Study in Museum J. Armand Bombardier

Han

Zhan

2021

Advances in Civil Engineering

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“…FWLBP (Roy et al, 2018), a hybrid of FD and LBP, is a robust, simple and an efficient method of describing the textures for large number of varied classes. FD (Panigrahy et al, 2020) is used to measure the degree of texture complexity, thus is a good indicator to analyse and classify the different textures. Moreover, its scale‐invariance property makes it a robust tool to resist the scale changes in the intensity surface of the texture images.…”

Section: Proposed Classification Systemsmentioning

confidence: 99%

“…varied classes. FD(Panigrahy et al, 2020) is used to measure the degree of texture complexity, thus is a good indicator to analyse and classify the T A B L E 3 RQA measures selected using RFE-RF Feature selection for RQA measures using RFE-RF (five-fold CV) based on F1-macro score different textures. Moreover, its scale-invariance property makes it a robust tool to resist the scale changes in the intensity surface of the texture images.…”

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confidence: 99%

EEG‐based automatic multi‐class classification of epileptic seizure types using recurrence plots

2021

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There is an urgent need to develop an efficient system for accurate recognition of epileptic seizure type that could play a significant role in reducing the adversial effects of the disease. A lot of work is available for EEG based automatic seizure detection but very less attempts have been made towards the classification of variants of seizures. Moreover, none of the authors have included the EEG signals for myoclonic seizure type in their classification studies. Our study aims to propose the automatic machine learning based multi-class classification system for classifying six types of epileptic seizures (such as absence, focal non-specific, complex-partial, generalized, tonic-clonic and including myoclonic too) through the use of recurrence plots (RPs). In our study, we have collected 19-channel EEG data from a huge database of Temple University Hospital. Two classification modalities have been proposed depending upon the feature extraction approach followed for RPs-(a) Traditional approach using the recurrence quantification analysis (RQA) method;(b) Texture based approach using the hybrid method named as Unthresholded Recurrence Plot with Fractal Weighted Local Binary Pattern (URP-FWLBP), that has been proposed in our work using a combination of Unthresholded RPs (URPs) and Fractal Weighted Local Binary Pattern (FWLBP) method. Thereby, an indirect variant of support vector machine (one-vs-rest approach) has been used as the multi-class classifier in both the approaches. The performance of the proposed modalities has been validated using five-fold cross-validation method in the light of seven metrics-accuracy, sensitivity, specificity, Matthews correlation coefficient, geometric-mean, precision and f1-score. The experimental results show the effectiveness of the proposed system following hybrid URP-FWLBP method in performing multi-class epileptic seizure type classification with 100% efficiency, thereby outperforming the traditional RQA method based system as well the existing state-of-the-art systems.

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“…In 2017 [ 27 ], they investigated the effect of box height on the accuracy of DBC computation and presented a new method of calculating box height, which considerably enhanced the accuracy of fractal dimension calculation. In 2020 [ 28 ], they proposed three new DBC algorithms based on weighted least squares regression. These methods also use a new xy -plane shifting mechanism and a modified formula for computing n r .…”

Section: Introductionmentioning

confidence: 99%

“…Currently, this strategy is frequently used in studies of state-of-the-art DBC methods [ 22 , 26 , 30 , 31 ]. However, in other works, such as those of Liu et al [ 25 ] and Panigrahy et al [ 28 ], the authors utilized a similar approach to that used in Biswas’ study [ 32 ], employing divisors of the image size as the grid size s to partition the square image fully.…”

Section: Introductionmentioning

confidence: 99%

Problems of the Grid Size Selection in Differential Box-Counting (DBC) Methods and an Improvement Strategy

Jiang

Liu

et al. 2022

Entropy

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The differential box-counting (DBC) method is useful for determining the fractal dimension of grayscale images. It is simple to learn and implement and has been extensively utilized. However, this approach has several problems, such as over- or undercounting the number of boxes due to inappropriate parameter choices, limiting the calculation accuracy. Many studies have been conducted to increase the algorithm’s computational accuracy by improving the calculating parameters of the differential box-counting method. The grid size is a crucial parameter for the DBC method. Generally, there are two typical ways for selecting the grid size in relevant studies: consecutive integer and divisors of image size. However, both methods for grid size selection are problematic. The consecutive integer method cannot partition the image entirely and will result in the undercounting of boxes; the divisors of image size can partition the image completely. However, this method uses fewer grid sizes to compute fractal dimensions and has a relatively huge distance error (DE). To address the shortcomings of the above-mentioned two approaches, this research presents an improved grid size selection strategy. The improved method enhances computational accuracy by computing the discarded image edge areas in the consecutive integer method, allowing the original image information to be used as thoroughly as the divisor strategy. Based on fractional Brownian motion (FBM), Brodatz, and Aerials image sets, the accuracy of the three grid size selection techniques (consecutive integer method, divisors of image size method, and the improved algorithm) to compute the fractal dimension is then compared. The results reveal that, compared to the two prior techniques, the revised algorithm described in this study minimizes the distance error and increases the accuracy of the fractal dimension computation.

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Image texture surface analysis using an improved differential box counting based fractal dimension

Cited by 32 publications

References 39 publications

Fractal-Dimension-Based Walking Trajectory Analysis: A Case Study in Museum J. Armand Bombardier

Fractal-Dimension-Based Walking Trajectory Analysis: A Case Study in Museum J. Armand Bombardier

EEG‐based automatic multi‐class classification of epileptic seizure types using recurrence plots

Problems of the Grid Size Selection in Differential Box-Counting (DBC) Methods and an Improvement Strategy

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