Automatic Detection System of Olive Trees Using Improved K-Means Algorithm

Abstract

Olive cultivation over the past few years has spread across Mediterranean countries with Spain being the world’s largest olive producer among them. Because olives are a major part of the economy for such countries keeping records of their tree count and crop yield is of high significance. Manual counting of trees over such large areas is humanly infeasible. To address this problem, we propose an automatic method for the detection and enumeration of olive trees. The algorithm is a multi-step classification system comprising pre-processing, image segmentation, feature extraction, and classification. RGB satellite images were acquired from the Spanish territory and pre-processed to suppress the additive noise. The region of interest was then segmented from the pre-processed images using K-Means segmentation, through which statistical features were extracted and classified. Promising results were achieved for all classifiers, namely Naive Bayesian, Support Vector Machines (SVMs), Random Forest and Multi-Layer Perceptrons (MLPs), at various division ratios of data samples. In a comparison of all the classification algorithms, Random Forest outperformed the rest by an overall accuracy of 97.5% at the division ratio of 70 to 30 for training to testing.

Data Optimization Analysis of Integrated Energy System Based on K -Means Algorithm

“…In addition, under the new market situation that China's power generation enterprises implement the separation of plant and network and price competition on the Internet, it is imperative to vigorously develop combustion optimization technology in order to obtain higher economic benefits and enhance their market competitiveness [10]. The boiler combustion optimization guidance system developed in China monitors the changes of boiler combustion efficiency online by monitoring important parameters such as wind speed and pulverized coal concentration, so as to guide the operation of boiler operators [11]. In addition, the neural network model and nonlinear optimization technology are adopted to guide the boiler combustion adjustment, and the model self-correction technology is adopted to realize the long-term effectiveness of the boiler combustion system.…”

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A Large-Scale Dataset and Deep Learning Model for Detecting and Counting Olive Trees in Satellite Imagery

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