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There is a high demand for detecting defects on the surface of objects. In industry, inspecting mass-produced items is costly and labor-intensive. This paper introduces an automatic defect detection method. Specifically, the method detects defects ...

Autonomous vehicles make decisions and controls based on various object recognition results. The driving environment is characterized by the coexistence of a multitude of objects of varying shapes and sizes. Therefore, the ability to accurately recognise ...

With the continuous development of computer vision, the application of image recognition technology is becoming increasingly widespread. An edge detection image recognition model based on improved artificial bee colony algorithm has been proposed. ...

In the maritime context, the delineation of the sea-sky line, serving as a critical demarcation between the maritime and non-maritime domains, assumes paramount significance for target detection and the preservation of situational awareness. Despite this, ...

With the automobile becoming an indispensable means of travel in our daily life, road traffic accidents are becoming an increasingly serious social problem. In order to improve the driving safety of vehicles, the vehicle driving assistance system based ...

Achieving high‐precision extraction of sea islands from high‐resolution satellite remote sensing images is crucial for effective resource development and sustainable management. Unfortunately, achieving such accuracy for sea island extraction ...

Automatic image thresholding is commonly used in the area of computer vision and pattern recognition for object detection. This research work proposes a new method of lesion detection in dermoscopic images using an optimal threshold based on the Newton-...

The colony is one of the important research objects in microbial technology, which can realize the evaluation of food safety level, environmental pollution degree, therapeutic effect of medical drugs, and characteristics of agricultural fungicides. ...

In recent years, the development of various visual sensing and image analysis techniques has resulted in the creation of images that contain extremely sensitive data. Unauthorised individuals who access this data illegally risk capturing and disclosing ...

Estimating surface normals from 3D point clouds is critical for various applications, including surface reconstruction and rendering. While existing methods for normal estimation perform well in regions where normals change slowly, they tend to fail ...

Relying on large-scale training data with pixel-level labels, previous edge detection methods have achieved high performance. However, it is hard to manually label edges accurately, especially for large datasets, and thus the datasets inevitably contain ...

Edge detection, as a core component in a wide range of vision-oriented tasks, is to identify object boundaries and prominent edges in natural images. An edge detector is desired to be both efficient and accurate for practical use. To achieve the goal, ...

In recent years, the accuracy of edge detection on several benchmarks has been significantly improved by deep learning based methods. However, the prediction of deep neural networks is usually blurry and needs further post-processing including non-...

This paper applied grayscale histogram feature extraction to analyse a medical image of tuberculosis lungs. Five different edge detection methods, namely Roberts, Sobel, Prewitt, Canny, and LoG algorithms were used to realise the feature extraction of ...

At present, the local appearance-based texture descriptors in Facial Expression Recognition have limited accuracy due to the inability to encode the discriminative edges. The major cause is the presence of distorted and weak edges due to noise. Hence, ...

In recent decades, image processing technology has made significant advancements, but low-frequency images still pose challenges for analysis. To address this issue, we propose a novel edge detection filter based on fractional order orthogonal Legendre-...

Geodesic active contour model (GACM) is a standard deterministic method for the segmentation of complex organ structures based on edge maps. For MRI images, the GACM performs poorly due to noise and weak edges, which might result from a low scanning ...

Edge detection is one of the basic challenges in the field of computer vision. The results of most recent methods produce thick edges and background interference. The images generated by these networks must be postprocessed with non-maximum suppression (...

Medical imaging modalities play a vital role in the healthcare sector for disease diagnosis and prediction. Optical Coherence Tomography uses near-infrared rays for generating cross-sectional images of the retina. Edge detection is a ...

In this paper, a novel and highly efficient inexact Full Adder cell by exploiting two logic styles including conventional CMOS (C-COMS) and pass transistor logic (PTL) are presented. The so-called carbon nanotube field-effect transistor (CNFET) technology ...