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首页> 外文期刊>International Journal of Innovative Computing Information and Control >QUALITY ANALYSIS AND ILLEGAL LOGGING IMAGE DETECTION USING SYARITAR METHOD
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QUALITY ANALYSIS AND ILLEGAL LOGGING IMAGE DETECTION USING SYARITAR METHOD

机译：SYARITAR法进行质量分析和非法记录图像检测

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摘要

The activity of illegal logging causes great losses related to economy, ecology and loss of natural balance due to the disruption of the natural functions of forests. Therefore, the establishment of logging detection systems is useful for assisting government policy, especially in the forest preservation program based on remote sensing technology. In this study, the detection of illegal logging is developed by using Discrete Cosine Transform-Hidden Markov Model (DCT-HMM), which is called Syaritar method in this paper. In this method, the stages of image processing systems utilize the selection index of which values are taken from an RGB image that is previously being extracted from the DCT-HMM process. The data samples for testing image are taken from protected forest areas in Sumatera (Lahat region) Indonesia with the size of 84×84m~2 considering image data pairs in 2006, 2007 and 2009 as initial and final data, respectively. The identification results provide the level of accuracy in illegal logging detection activity of 77.76%.
机译：由于森林自然功能的破坏，非法伐木活动造成与经济，生态和自然平衡有关的巨大损失。因此，建立测井探测系统对于协助政府政策特别是在基于遥感技术的森林保护计划方面很有用。本文利用离散余弦变换隐马尔可夫模型（DCT-HMM）开发了检测非法日志的方法，本文将其称为Syaritar方法。在这种方法中，图像处理系统的各个阶段利用选择索引，该选择索引的值取自先前从DCT-HMM处理中提取的RGB图像。用于测试图像的数据样本取自印度尼西亚苏门答腊（拉哈特地区）受保护的森林区域，大小为84×84m〜2，分别将2006年，2007年和2009年的图像数据对作为初始和最终数据。识别结果提供了77.76％的非法日志检测活动的准确度。

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