Color Region Classification of Flue-cured Tobacco Leaves Based on the Image Processing and Support Vector Machine

Pan, Zhi-Li; Meng, Qing-Hao; Wei, Chunyang; Li, Feng; Shixiang, Zhang; Wang, Jianwei; Guo, Weimin; Ai, Zhilu

doi:10.3724/sp.j.1006.2012.00374

Cited by 5 publications

(2 citation statements)

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“…Therefore, before extracting color features, image preprocessing should be done in Visual Studio. The use of wavelet method can remove interference of noise information of images, removal of image background can be done by using class difference image method [14].…”

Section: Preprocessing Of Tobacco Leaves Imagementioning

confidence: 99%

Extraction of Tobacco Leaves Color Features Based on HSI Color Space

Deng

et al. 2014

AMM

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Tobacco is widely planted worldwide as an important economic crop. The differences of planting environment and growth status in different regions lead to different levels of tobacco quality, while color is one of the important indexes to evaluate the quality grade of tobacco leaves. Even for those that are planted in the same area, colors of different grades of tobacco leaves vary greatly, so the color of tobacco leaves is often used as the main evaluating index in tobacco leaves grading. In this paper color extraction of standard tobacco leaves based on HSI color space was thoroughly studied. H, S and I component would be quantified and extracted by using color histogram, then the average value corresponding to every color component was calculated. After extraction and calculation on the same level of standard tobacco leaves, the ranges of three color components could be obtained in HSI color space by using statistical method, and provide data information for tobacco leaves grading.

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Section: Preprocessing Of Tobacco Leaves Imagementioning

confidence: 99%

Extraction of Tobacco Leaves Color Features Based on HSI Color Space

Deng

et al. 2014

AMM

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“…Color recognition: To identify the color of an object, some preprocessing of the image is needed and the color features are extracted. In some documents, color features of tobacco leaves are obtained by using Region Growing Method in the pre-processing and region classification is done by using Support Vector Machine (SVM) (Pan et al, 2012). As a fact that the tobacco leaves may crinkle in the curing process, the wrinkles and the stem of the leaf can not be used to identify the color of the leaf.…”

Section: Color Recognitionmentioning

confidence: 99%

Intelligent Tobacco Curing Control Based on Color Recognition

Zhang¹,

Jiang²,

Chen³

2013

RJASET

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To reduce the labor cost and the workload required in the tobacco curing process, an intelligent tobacco curing control technique adopting color identification of the tobacco leaves is proposed. The HSI color space is used in color segmentation and the color recognition with fuzzy decision is used in the curing process. The curing controller can identify the curing stage by the color features of the tobacco leaves and the environmental parameters of the barn. Then it adjusts the temperature, the humidity and the ventilation of the barn to prevent the leaves from bad colors. The controller can be used for various tobacco species and various mature states and harvesting weather. The intelligent control can reduce the workload and labor cost involved in the curing process and guarantee the quality and market value of the cured tobacco.

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A novel intelligent control system for flue-curing barns based on real-time image features

Yang

Tian

2014

Biosystems Engineering

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Color Region Classification of Flue-cured Tobacco Leaves Based on the Image Processing and Support Vector Machine

Cited by 5 publications

References 0 publications

Extraction of Tobacco Leaves Color Features Based on HSI Color Space

Extraction of Tobacco Leaves Color Features Based on HSI Color Space

Intelligent Tobacco Curing Control Based on Color Recognition

A novel intelligent control system for flue-curing barns based on real-time image features

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