REGISTRATION METHOD OF BACK-END COMMODITY OF SELF-CHECKOUT SYSTEM

• Main Authors: CHEN PO-HSIANG, CHIEW JUN CHUAN, ZHAO KAI-WEN, HSIEH SHAO-HANG
• Format: Patent
• Language: English; Japanese
• Published: 08.04.2021
• Subjects: CALCULATING; CHECKING-DEVICES; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; PHYSICS; REGISTERING THE RECEIPT OF CASH, VALUABLES, OR TOKENS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

To provide a method for registering a back-end commodity of a self-checkout system capable of supporting a user to register a new commodity in a self-checkout system only with a small amount of commodity photograph.SOLUTION: A method for registering a back-end commodity of a self-checkout system includes following steps: taking a commodity photo of a commodity to be registered; performing a deformation process to the commodity photo on the basis of default parameters for generating a plurality of simulated photos; comparing the commodity photo as well as the multiple simulated photos with the plurality of photos in a database respectively by a well-trained convolutional neural networks (CNN) model and generating recognition rate; adding the commodity photo to an identification package for completing registration operation of the commodity if it is determined that the recognition rate satisfies a threshold value; and requesting a user to take again another commodity photo if it is determined that the recognition rate does not satisfy the threshold value.SELECTED DRAWING: Figure 4 【課題】ユーザが少量の商品写真だけで新しい商品をセルフチェックアウトシステムに登録することを支援可能なセルフチェックアウトシステムのバックエンド商品の登録方法を提供する。【解決手段】セルフチェックアウトシステムのバックエンド商品の登録方法は、登録しようとする商品の商品写真を撮影するステップと、デフォルトパラメータに基づいて商品写真を変形処理して、複数のシミュレーション写真を生成するステップと、学習済みの畳み込みニューラルネットワーク（ＣＮＮ）モデルによって商品写真及び複数のシミュレーション写真と、データベース内の複数の写真とをそれぞれ対比し、認識率を生成するステップと、認識率が閾値を満たすと判定した場合、商品写真を識別パッケージに追加して、商品の登録動作を完了するステップと、認識率が閾値を満たさないと判定した場合、商品写真を再撮影するように要求するステップと、を含む。【選択図】図４