IMAGE INSPECTION SYSTEM, IMAGE INSPECTION METHOD AND COMPUTER PROGRAM

• Main Authors: NIWA KOSUKE, TAKITO AZUMI, GENJIMA TATSUTO, SUGIURA NAOKUNI, YABUTA TAKATOSHI, TANAKA YOSHITAKA, TAKANO AZUSA, TAKAHASHI YUTA, HISATOMI SATOSHI, TAGASHIRA KEISHO
• Format: Patent
• Language: English; Japanese
• Published: 05.06.2023
• Subjects: CALCULATING; COMPUTING; COUNTING; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES; MEASURING; PHYSICS; TESTING

To provide an image inspection system, an image inspection method, and a computer program that improve the accuracy of image inspection of castings.SOLUTION: In an image inspection system 10, a control device 50 includes an image acquisition unit that acquires an inspection image obtained by imaging the casting that is the object to be inspected OB, and a plurality of castings that have been determined to be non-defective in advance. A storage unit that stores a feature amount extracted from each of the plurality of non-defective images obtained by using the first convolutional neural network that has been trained, and extracts the feature amount from an inspection image using a first convolutional neural network, using the feature amount extracted from the inspection image and the feature amount extracted from each of a plurality of non-defective product images, a degree of abnormality of the inspection image for the plurality of non-defective product images is calculated, and the casting of an inspection target is performed based on a degree of abnormality of the inspection image, and a first determination unit that determines whether the product is good or bad.SELECTED DRAWING: Figure 1 【課題】鋳造品の画像検査の精度を向上させる画像検査システム、画像検査方法及びコンピュータプログラムを提供する。【解決手段】画像検査システム１０において、制御装置５０は、検査対象物ＯＢである鋳造品を撮像することにより得られる検査画像を取得する画像取得部と、予め良品と判定された複数の鋳造品を撮像することにより得られる複数の良品画像のそれぞれから学習済みの第１畳み込みニューラルネットワークを用いて抽出された特徴量を記憶する記憶部と、第１畳み込みニューラルネットワークを用いて検査画像から特徴量を抽出し、検査画像から抽出した特徴量と複数の良品画像の夫々から抽出された特徴量とを用いて複数の良品画像に対する検査画像の異常度を算出し、検査画像の異常度に基づいて検査対象の鋳造品の良否を判定する第１判定部と、を備える。【選択図】図１