Plant recognition based on Jaccard distance and BOW

Wang, Zhaobin; Cui, Jing; Zhu, Ying

doi:10.1007/s00530-020-00657-6

Cited by 4 publications

(2 citation statements)

References 35 publications

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“…Because the number of feature points extracted from different images is different, DTORB feature points extracted from sample images cannot be used directly for the training of learning machines. Therefore, our proposed algorithm combines BoW with the DTORB feature extraction algorithm to extract feature vectors [20].…”

Section: Proposed Methodsmentioning

confidence: 99%

Small insulator target detection based on multi‐feature fusion

Tang

Liang

Qiu

2023

IET Image Processing

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The proportion of insulators in aerial power patrol images is small and the background of overhead lines is complex, often leading to incomplete and inaccurate detection of insulators. Therefore, an algorithm for detecting insulator targets based on multi‐feature fusion is developed in this study. Firstly, a dynamic threshold oriented fast and rotated brief algorithm is proposed, which uses the bag‐of‐words dictionary model to determine local shape features of the image, applies gradient weighting to the global texture feature vector extracted by the histogram of oriented gradients algorithm and performs radial gradient transformations to get the improved HOG of features. Secondly, the feature vectors are fused serially, the learning machine is trained and the parameters of the support vector machine are optimized using the quantum particle swarm optimization algorithm. Finally, the target area is pre‐divided by the selective search algorithm, and the area is classified by the learning machine. The experimental results show that the proposed feature extraction method can describe the image details more accurately than the existing methods, and the average accuracy of the feature extraction classifier can reach 93.7%, which helps to overcome the incomplete detection problem of insulator detection at the aerial work site.

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Section: Proposed Methodsmentioning

confidence: 99%

Small insulator target detection based on multi‐feature fusion

Tang

Liang

Qiu

2023

IET Image Processing

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“…Currently, there are extensive studies on the BOW model. As one of the feature encoding algorithms in the aspect of image retrieval and text processing, the BOW model can be effectively applied to image classification [21,22] and object recognition [23,24]. Zou et al [25] proposed an SVM-based image classification method through an improved BOW model and combined it with context information to generate middle-level semantic features.…”

Section: Related Workmentioning

confidence: 99%

Exploring the topic evolution of Dunhuang murals through image classification

Zeng

Sun

et al. 2022

Journal of Information Science

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Dunhuang is a unique art treasure and a world heritage site. In order to organise and manage Dunhuang cultural heritage resources, this article studies the classification of Dunhuang murals in different dynasties, and explores the topic distribution characteristics and evolution rules of them. First, image features are extracted through scale-invariant feature transform (SIFT) and Canny and scale-invariant feature transform (CSIFT), a visual dictionary is generated through the k-means clustering algorithm, and the term frequency–inverse document frequency (TF-IDF) vector is calculated and combined with the colour feature vector extracted via hue, saturation and value (HSV). Second, Dunhuang mural images are collected and the support vector machine (SVM) classifier is built. Finally, the knowledge graph-based topic maps are constructed, and graph theory is introduced to analyse the topic distribution and evolution of Dunhuang murals in different dynasties. The results show that the Dunhuang murals of different dynasties can be effectively classified through the bag of words, HSV and support vector machine (BOW_HSV_SVM) based on their visual features. Through topic maps, the topic distribution characteristics and evolution rules of Dunhuang murals with the dynasties are revealed.

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BCMask: a finer leaf instance segmentation with bilayer convolution mask

Zhu

Ren

et al. 2022

Multimedia Systems

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Plant recognition based on Jaccard distance and BOW

Cited by 4 publications

References 35 publications

Small insulator target detection based on multi‐feature fusion

Small insulator target detection based on multi‐feature fusion

Exploring the topic evolution of Dunhuang murals through image classification

BCMask: a finer leaf instance segmentation with bilayer convolution mask

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