Speed-up Feature Detector using Adaptive Accelerated Segment Test

Biadgie, Yenewondim; Sohn, Kyung-Ah

doi:10.1080/02564602.2015.1103669

Cited by 5 publications

(3 citation statements)

References 19 publications

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“…P's grayscale value is set as Ip. If there are n consecutive points in these 16 points with grayscale values higher than Ip or lower than Ip, the pixel point P is considered as a corner point [19].…”

Section: Improved Fast Corner Detection Algorithmmentioning

confidence: 99%

“…It is often used for rapid detection of corner point of the image. Based on FAST corner point detection, some methods propose fast feature detectors extract corner point feature information for image matching [19, 20]. Meanwhile, based on the adaptive threshold value of local region, some methods propose to filter the non‐corner region with the solid circle model, and then use the inner and outer edge to detect the corner point to improve the accuracy [21].…”

Section: Introductionmentioning

confidence: 99%

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Mobile terminal gesture recognition based on improved FAST corner detection

Jian

Xiang

Zhang

2019

IET Image Processing

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Section: Improved Fast Corner Detection Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mobile terminal gesture recognition based on improved FAST corner detection

Jian

Xiang

Zhang

2019

IET Image Processing

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“…Recently, we proposed an algorithm in [32] to detect higher order image structures such as edges and corners using a circular mask. In computer vision, many edge and corner detectors were developed using a circular mask [33,34,35].…”

Section: Determination and Quantization Of Prediction Refinement Contextmentioning

confidence: 99%

Multi-resolution Lossless Image Compression for Progressive Transmission and Multiple Decoding Using an Enhanced Edge Adaptive Hierarchical Interpolation

2017

KSII TIIS

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In a multi-resolution image encoding system, the image is encoded into a single file as a layer of bit streams, and then it is transmitted layer by layer progressively to reduce the transmission time across a low bandwidth connection. This encoding scheme is also suitable for multiple decoders, each with different capabilities ranging from a handheld device to a PC. In our previous work, we proposed an edge adaptive hierarchical interpolation algorithm for multi-resolution image coding system. In this paper, we enhanced its compression efficiency by adding three major components. First, its prediction accuracy is improved using context adaptive error modeling as a feedback. Second, the conditional probability of prediction errors is sharpened by removing the sign redundancy among local prediction errors by applying sign flipping. Third, the conditional probability is sharpened further by reducing the number of distinct error symbols using error remapping function. Experimental results on benchmark data sets reveal that the enhanced algorithm achieves a better compression bit rate than our previous algorithm and other algorithms. It is shown that compression bit rate is much better for images that are rich in directional edges and textures. The enhanced algorithm also shows better rate-distortion performance and visual quality at the intermediate stages of progressive image transmission.

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Stitching method for panoramic nail fold images based on capillary contour enhancement

Lin,

Yin,

et al. 2024

Journal of Biophotonics

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Nail fold capillaroscopy is an important means of monitoring human health. Panoramic nail fold images improve the efficiency and accuracy of examinations. However, the acquisition of panoramic nail fold images is seldom studied and the problem manifests of few matching feature points when image stitching is used for such images. Therefore, this paper presents a method for panoramic nail fold image stitching based on vascular contour enhancement, which first solves the problem of few matching feature points by pre‐processing the image with contrast‐constrained adaptive histogram equalization (CLAHE), bilateral filtering (BF), and sharpening algorithms. The panoramic images of the nail fold blood vessels are then successfully stitched using the fast robust feature (SURF), fast library of approximate nearest neighbors (FLANN) and random sample agreement (RANSAC) algorithms. The experimental results show that the panoramic image stitched by this paper's algorithm has a field of view width of 7.43 mm, which improves the efficiency and accuracy of diagnosis.

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Speed-up Feature Detector using Adaptive Accelerated Segment Test

Cited by 5 publications

References 19 publications

Mobile terminal gesture recognition based on improved FAST corner detection

Mobile terminal gesture recognition based on improved FAST corner detection

Multi-resolution Lossless Image Compression for Progressive Transmission and Multiple Decoding Using an Enhanced Edge Adaptive Hierarchical Interpolation

Stitching method for panoramic nail fold images based on capillary contour enhancement

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