基于多种花卉查询的花卉视频检索

IF 8.2 Q1 AGRICULTURE, MULTIDISCIPLINARY Artificial Intelligence in Agriculture Pub Date : 2021-01-01 DOI:10.1016/j.aiia.2021.11.001
V.K. Jyothi , V.N. Manjunath Aradhya , Y.H. Sharath Kumar , D.S. Guru
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引用次数: 0

摘要

从大量视频数据集合中搜索、识别和检索感兴趣的视频是一项即时要求。这一要求已被公认为计算机视觉、机器学习和模式识别领域的一个活跃研究领域。花卉视频识别和检索在花卉栽培和园艺领域至关重要。在本文中,我们提出了一个花的视频检索模型。最初,视频是用关键帧表示的,关键帧中的花朵是从背景中分割出来的。然后,从关键帧的花区域提取特征,对模型进行分析。线性判别分析(LDA)适用于判别特征的提取。应用多类别支持向量机(MSVM)分类器识别查询视频的类别。实验是在我们自己的相对较大的数据集上进行的,该数据集由7788个视频组成,这些视频是从三种不同的设备上拍摄的30种不同的花卉。通常,花视频的检索是通过使用由单个物种的花组成的查询视频来解决的。在这项工作中,我们试图开发一个系统,该系统包括对由不同物种的花朵组成的查询视频的相似视频的检索。
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Retrieval of flower videos based on a query with multiple species of flowers

Searching, recognizing and retrieving a video of interest from a large collection of a video data is an instantaneous requirement. This requirement has been recognized as an active area of research in computer vision, machine learning and pattern recognition. Flower video recognition and retrieval is vital in the field of floriculture and horticulture. In this paper we propose a model for the retrieval of videos of flowers. Initially, videos are represented with keyframes and flowers in keyframes are segmented from their background. Then, the model is analysed by features extracted from flower regions of the keyframe. A Linear Discriminant Analysis (LDA) is adapted for the extraction of discriminating features. Multiclass Support Vector Machine (MSVM) classifier is applied to identify the class of the query video. Experiments have been conducted on relatively large dataset of our own, consisting of 7788 videos of 30 different species of flowers captured from three different devices. Generally, retrieval of flower videos is addressed by the use of a query video consisting of a flower of a single species. In this work we made an attempt to develop a system consisting of retrieval of similar videos for a query video consisting of flowers of different species.

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来源期刊
Artificial Intelligence in Agriculture
Artificial Intelligence in Agriculture Engineering-Engineering (miscellaneous)
CiteScore
21.60
自引率
0.00%
发文量
18
审稿时长
12 weeks
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