Fourier Spectrum Image Texture Analysis

Hu, Xinyu; Ensor, Andrew

doi:10.1109/ivcnz.2018.8634740

Cited by 7 publications

(9 citation statements)

References 5 publications

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“…It also signals that a similar texture unit categorises every local texture of the given pixel. The popular Fourier transform (FT) of a particular region of interest (ROI) of an image transforms spatial information into a frequency domain where the spectrum contains the uniform texture image as well as its position [ 81 ]. The texture power spectrum (PS) is measured using different size ROIs [ 50 , 53 , 58 ] by Fourier transform, where different enhancement methods are used before calculating PS values.…”

Section: Analysis Of Returned Articlesmentioning

confidence: 99%

Computer-Aided Diagnosis of Coal Workers’ Pneumoconiosis in Chest X-ray Radiographs Using Machine Learning: A Systematic Literature Review

Devnath

Summons

Luo

et al. 2022

IJERPH

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Computer-aided diagnostic (CAD) systems can assist radiologists in detecting coal workers’ pneumoconiosis (CWP) in their chest X-rays. Early diagnosis of the CWP can significantly improve workers’ survival rate. The development of the CAD systems will reduce risk in the workplace and improve the quality of chest screening for CWP diseases. This systematic literature review (SLR) amis to categorise and summarise the feature extraction and detection approaches of computer-based analysis in CWP using chest X-ray radiographs (CXR). We conducted the SLR method through 11 databases that focus on science, engineering, medicine, health, and clinical studies. The proposed SLR identified and compared 40 articles from the last 5 decades, covering three main categories of computer-based CWP detection: classical handcrafted features-based image analysis, traditional machine learning, and deep learning-based methods. Limitations of this review and future improvement of the review are also discussed.

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Section: Analysis Of Returned Articlesmentioning

confidence: 99%

Computer-Aided Diagnosis of Coal Workers’ Pneumoconiosis in Chest X-ray Radiographs Using Machine Learning: A Systematic Literature Review

Devnath

Summons

Luo

et al. 2022

IJERPH

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show abstract

“…In image processing, texture is analyzed based on the variations in the gray tone values extracted from an image (Metre and Ghorpade, 2013). Texture features are commonly extracted using Gray Level Co-occurrence Matrix (GLCM) to find symmetry in the texture in an image (Hu and Ensor, 2019).…”

Section: Texture Feature Extractionmentioning

confidence: 99%

“…Local and global texture feature descriptors are obtained from the spectrum. Fourier spectrum descriptors describe the direction and formation of texture patterns (Hu and Ensor, 2019). For this study, a frequency of 2 was applied to each image to generate 8 spectral peaks and 16 texture descriptors.…”

Section: Extentmentioning

confidence: 99%

Estimation of Cold Stress, Plant Age, and Number of Leaves in Watermelon Plants Using Image Analysis

et al. 2022

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Watermelon (Citrullus lanatus) is a widely consumed, nutritious fruit, rich in water and sugars. In most crops, abiotic stresses caused by changes in temperature, moisture, etc., are a significant challenge during production. Due to the temperature sensitivity of watermelon plants, temperatures must be closely monitored and controlled when the crop is cultivated in controlled environments. Studies have found direct responses to these stresses include reductions in leaf size, number of leaves, and plant size. Stress diagnosis based on plant morphological features (e.g., shape, color, and texture) is important for phenomics studies. The purpose of this study is to classify watermelon plants exposed to low-temperature stress conditions from the normal ones using features extracted using image analysis. In addition, an attempt was made to develop a model for estimating the number of leaves and plant age (in weeks) using the extracted features. A model was developed that can classify normal and low-temperature stress watermelon plants with 100% accuracy. The R2, RMSE, and mean absolute difference (MAD) of the predictive model for the number of leaves were 0.94, 0.87, and 0.88, respectively, and the R2 and RMSE of the model for estimating the plant age were 0.92 and 0.29 weeks, respectively. The models developed in this study can be utilized in high-throughput phenotyping systems for growth monitoring and analysis of phenotypic traits during watermelon cultivation.

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“…These feature vectors are built upon the discrete 2dimensional Fourier Transform (2DFT). Feature vectors which include the use of the 2DFT from both a computer vision and texture analysis stand-point, have been shown to provide standalone and complementary results to spatially focused approaches [8]. For example, the 2DFT distinguishes between material textures and objects in non-contextual [9], [10] and contextual images [11] in conjunction with a standalone classifier [12] or input to a neural network [13], [14].…”

Section: Introductionmentioning

confidence: 99%

Image-based material analysis of ancient historical documents

Reynolds¹,

Dhali²,

Schomaker³

2022

Preprint

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Researchers continually perform corroborative tests to classify ancient historical documents based on the physical materials of their writing surfaces. However, these tests, often performed on-site, requires actual access to the manuscript objects. The procedures involve a considerable amount of time and cost, and can damage the manuscripts. Developing a technique to classify such documents using only digital images can be very useful and efficient. In order to tackle this problem, this study uses images of a famous historical collection, the Dead Sea Scrolls, to propose a novel method to classify the materials of the manuscripts. The proposed classifier uses the two-dimensional Fourier Transform to identify patterns within the manuscript surfaces. Combining a binary classification system employing the transform with a majority voting process is shown to be effective for this classification task. This pilot study shows a successful classification percentage of up to 97% for a confined amount of manuscripts produced from either parchment or papyrus material. Feature vectors based on Fourier-space grid representation outperformed a concentric Fourier-space format.

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Fourier Spectrum Image Texture Analysis

Cited by 7 publications

References 5 publications

Computer-Aided Diagnosis of Coal Workers’ Pneumoconiosis in Chest X-ray Radiographs Using Machine Learning: A Systematic Literature Review

Computer-Aided Diagnosis of Coal Workers’ Pneumoconiosis in Chest X-ray Radiographs Using Machine Learning: A Systematic Literature Review

Estimation of Cold Stress, Plant Age, and Number of Leaves in Watermelon Plants Using Image Analysis

Image-based material analysis of ancient historical documents

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