PLANTED TREE AUTOMATIC DETECTION DEVICE, PLANTED TREE AUTOMATIC DETECTION METHOD AND PROGRAM

• Main Authors: DENG SONGQIU, FUJIHIRA MITSUKI, TAKENAKA YUKI, KATO MASATO, NAKAGAWA HIROTO
• Format: Patent
• Language: English; Japanese
• Published: 31.10.2022
• Subjects: AGRICULTURE; ANIMAL HUSBANDRY; CALCULATING; COMPUTING; COUNTING; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPSOR SEAWEED; FISHING; FORESTRY; GYROSCOPIC INSTRUMENTS; HORTICULTURE; HUMAN NECESSITIES; HUNTING; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; MEASURING; MEASURING DISTANCES, LEVELS OR BEARINGS; NAVIGATION; PHOTOGRAMMETRY OR VIDEOGRAMMETRY; PHYSICS; SURVEYING; TESTING; TRAPPING; WATERING

To automatically detect a planted tree with high accuracy.SOLUTION: A planted tree automatic detection device creates a preprocessed aerial photographed image data from aerial photographed color image data of a forest area, removes noise included in the preprocessed aerial photographed image data to create noise-removed aerial photographed image data, detects planted tree candidate points based on the preprocessed aerial photographed image data and the noise-removed aerial photographed image data to create planted tree candidate point detection image data including the planted tree candidate points, extracts a feature amount from a predetermined area including the planted tree candidate points in the planted tree candidate point detection image data to create planted tree detection data, and detects a planted tree included in the aerial photographed color image data based on the planted tree detection data. The planted tree automatic tree detection device divides the planted tree detection data into estimation data and training data, constructs an estimation model by supervised learning using the training data, evaluates the accuracy of the estimation model, and performs the estimation of the planted tree included in the estimation model using the estimation model selected based on an accuracy evaluation result of the estimation model.SELECTED DRAWING: Figure 1 【課題】植栽木を高精度に自動検出する。【解決手段】森林域の空撮カラー画像データから前処理後空撮画像データを作成し、前処理後空撮画像データに含まれるノイズを除去してノイズ除去後空撮画像データを作成し、前処理後空撮画像データとノイズ除去後空撮画像データとに基づいて植栽木候補点を検出して植栽木候補点を含む植栽木候補点検出画像データを作成し、植栽木候補点検出画像データのうちの植栽木候補点を含む所定領域から特徴量を抽出して植栽木検出用データを作成し、植栽木検出用データに基づいて空撮カラー画像データに含まれる植栽木を検出する植栽木自動検出装置は、植栽木検出用データを推定用データと訓練用データとに分割し、訓練用データを用いた教師あり学習によって推定モデルを構築し、推定モデルの精度評価を実行し、推定モデルの精度評価の結果に基づいて選定された推定モデルを用いて推定用データに含まれる植栽木を推定する。【選択図】図１