Desease Identification In Plant Leaf Image of Chili (Capsicum Annum (L)) Using Image Processing and Automated Colour Equalization (ACE) Algorithm

Basiroh Basiroh
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Abstract

The world of agriculture becomes one of the vital objects and one of the promising business prospects. To obtain optimal agricultural yield, the process of plant care and the way of planting should be really - maximal, because the main key in seeking maximum results in terms of quality and quantity. Harvest failures are the least desirable to farmers and crop failures are the number one scariest specter for cultivating farmers. Today's informatics technology has been developed in an effort to support increased yields in the agricultural sector. This study measured the level of accuracy of results ekstraksi texture and colour feature. This research method using SVM classification ( Support Vector Machine ) seeks image processing through analyzing with Automated Color Equalization (ACE). With this method the accuracy of the extraction results a combination of 80% texture features, color feature extraction, and a combination of 80% color feature texture
基于图像处理和自动色彩均衡(ACE)算法的辣椒(Capsicum Annum (L))叶片图像病害识别
农业成为世界上最重要的对象之一,也是最具发展前景的产业之一。为了获得最佳的农业产量,植物养护的过程和种植的方式应该真正最大化,因为在质量和数量上寻求最大结果的主要关键。对农民来说,歉收是最不可取的,而对农民来说,歉收是最可怕的幽灵。今天的信息技术的发展是为了支持农业部门增加产量。本研究测量了纹理和颜色特征结果的准确性水平。该研究方法采用支持向量机(SVM)分类,通过自动色彩均衡(ACE)的分析来寻求图像处理。采用该方法提取精度为80%纹理特征组合、颜色特征提取、80%颜色特征组合的纹理
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