TW202232400A - Intelligent logistics data collection system - Google Patents
Intelligent logistics data collection system Download PDFInfo
- Publication number
- TW202232400A TW202232400A TW110104201A TW110104201A TW202232400A TW 202232400 A TW202232400 A TW 202232400A TW 110104201 A TW110104201 A TW 110104201A TW 110104201 A TW110104201 A TW 110104201A TW 202232400 A TW202232400 A TW 202232400A
- Authority
- TW
- Taiwan
- Prior art keywords
- image
- data collection
- collection system
- intelligent logistics
- plates
- Prior art date
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/103—Workflow collaboration or project management
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Development Economics (AREA)
- Game Theory and Decision Science (AREA)
- Educational Administration (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Data Mining & Analysis (AREA)
- Flow Control (AREA)
- Image Processing (AREA)
Abstract
Description
本發明是關於一種智能物流資料採集系統,特別是關於一種影像分析程序來計算板材數量的智能物流資料採集系統。The invention relates to an intelligent logistics data acquisition system, in particular to an intelligent logistics data acquisition system for calculating the number of plates by an image analysis program.
對於產線上各種板件的傳送,在不同站別之間需要統計傳送的板件數量,記錄每一站別輸入及移出板件數量的物流資料,可以追蹤製造的進度與完成數量,對於生產管理上是相當重要的資訊。但若是在每一物流點都以人工方式來數板,會耗費過多人力成本,在工作效率及數量正確率上都難以達到需求的標準。For the transfer of various boards on the production line, the number of boards transferred between different stations needs to be counted, and the logistics data of the number of boards input and removed at each station can be recorded. The above is quite important information. However, if the boards are counted manually at each logistics point, it will cost too much labor, and it will be difficult to meet the required standards in terms of work efficiency and quantity accuracy.
在某些產線或機台上,會以板材堆疊的厚度方式來估計板材數量,但板材堆疊方式與密度等差異都會造成預估的數量與實際數量有所差異,難以真正達到計數的成果,對於可判斷的板件數量也有所限制。在各種板材的材料、材質、厚度等不斷依產品改變的情況下,上述計數方式,都難以達到收集物流資料的需求。In some production lines or machines, the number of plates is estimated by the thickness of the plate stacking, but the difference in plate stacking method and density will cause the estimated number to be different from the actual number, and it is difficult to truly achieve the result of counting. There are also restrictions on the number of plates that can be judged. Under the circumstance that the material, material and thickness of various plates are constantly changing according to the product, the above counting methods are difficult to meet the needs of collecting logistics data.
有鑑於此,目前物流資料採集的系統有其侷限性,為了能針對各種板材數量進行檢測,本發明之發明人思索並設計一種智能物流資料採集系統,針對現有技術之缺失加以改善,進而增進產業上之實施利用。In view of this, the current logistics data collection system has its limitations. In order to detect the quantity of various plates, the inventors of the present invention have considered and designed an intelligent logistics data collection system to improve the deficiencies of the existing technology, thereby enhancing the industry. Use the above implementation.
有鑑於上述習知技術之問題,本發明之目的就是在提供一種智能物流資料採集系統,以解決習知之物流資料收集難以準確即迅速對板材進行計數之問題。In view of the above-mentioned problems of the prior art, the purpose of the present invention is to provide an intelligent logistics data collection system to solve the problem that the conventional logistics data collection is difficult to accurately count the plates.
根據本發明之一目的,提出一種智能物流資料採集系統,其包含板材輸送裝置、影像擷取裝置、影像處理裝置以及資料輸出裝置。其中板材輸送裝置包含承載區域以放置待測板材。影像擷取裝置設置朝向承載區域,拍攝待測板材的原始影像。影像處理裝置連接於影像擷取裝置,接收原始影像,影像處理裝置包含處理器及記憶體,原始影像儲存於記憶體,處理器存取記憶體以執行板材計數程序,分析原始影像以計算待測板材的板材數量。資料輸出裝置連接於影像處理裝置,將板材數量輸出。According to an objective of the present invention, an intelligent logistics data collection system is provided, which includes a plate conveying device, an image capturing device, an image processing device and a data output device. The plate conveying device includes a bearing area for placing the plate to be tested. The image capture device is set to face the bearing area, and captures the original image of the plate to be tested. The image processing device is connected to the image capture device and receives the original image. The image processing device includes a processor and a memory. The original image is stored in the memory. The processor accesses the memory to execute the plate counting program, analyzes the original image to calculate the test The number of sheets for the sheet. The data output device is connected to the image processing device, and outputs the number of plates.
較佳地,板材計數程序可包含由處理器執行以下的複數個運算模組:背景分離模組、特徵增強模組、區域分割模組、脊線影像模組以及板數分析模組。其中,背景分離模組將原始影像進行切割,背景分離以取得待分析影像。特徵增強模組將待分析影像經由形態學處理將表面平滑化降低噪訊,移除陰影邊界後再藉由色彩空間轉換產生特徵增強影像。區域分割模組將特徵增強影像進行切割後以訊號雜訊比過濾影像而產生複數個低雜訊影像區段。脊線影像模組將複數個低雜訊影像區段進行影像復原處理及二分類分割處理以得到複數個穩定脊線分布影像區段。板數分析模組統計複數個穩定脊線分布影像區段的脊線數以計算複數個區段板材數量,以複數個區段板材數量當中輸出重複次數最多的數量作為信置度最佳之板材數量,當此值有多個解時,即代表影像大部分區域雜訊是無法濾除與過於模糊,即須重新取像。Preferably, the plate counting program may include a plurality of operation modules executed by the processor: a background separation module, a feature enhancement module, a region segmentation module, a ridge line image module, and a plate number analysis module. The background separation module cuts the original image and separates the background to obtain the image to be analyzed. The feature enhancement module smoothes the surface of the image to be analyzed to reduce noise through morphological processing, removes the shadow boundary, and then generates a feature enhanced image through color space conversion. The region segmentation module cuts the feature-enhanced image and then filters the image with a signal-to-noise ratio to generate a plurality of low-noise image segments. The ridge line image module performs image restoration processing and two-class segmentation processing on the plurality of low-noise image segments to obtain a plurality of stable ridge line distribution image segments. The plate number analysis module counts the number of ridges in a plurality of stable ridge distribution image segments to calculate the number of plates in multiple segments, and takes the number of plates with the most repetitions among the number of plates in multiple segments as the plate with the best confidence. When there are multiple solutions for this value, it means that the noise in most areas of the image cannot be filtered out and is too blurred, that is, the image needs to be re-acquired.
較佳地,待測板材可包含複數個印刷電路板,複數個印刷電路板包含固定件,固定件將待測板材定位於承載區域。Preferably, the plate to be tested may include a plurality of printed circuit boards, and the plurality of printed circuit boards include a fixing member, and the fixing member positions the plate to be measured in the bearing area.
較佳地,板材輸送裝置可包含輸送帶或運送推車。Preferably, the sheet transport device may comprise a conveyor belt or a transport trolley.
較佳地,影像擷取裝置可包含固定式相機及光源,朝向承載區域以拍攝原始影像。Preferably, the image capturing device may include a fixed camera and a light source, facing the bearing area to capture the original image.
較佳地,影像擷取裝置可通過無線網路傳輸方式將原始影像即時傳送至影像處理裝置。Preferably, the image capturing device can transmit the original image to the image processing device in real time by means of wireless network transmission.
較佳地,資料輸出裝置可包含顯示器,板材數量顯示於顯示器。Preferably, the data output device may include a display, and the number of plates is displayed on the display.
較佳地,資料輸出裝置可包含移動裝置,板材數量通過無線網路傳輸方式回傳至移動裝置,顯示於移動裝置的顯示螢幕。Preferably, the data output device may include a mobile device, and the number of sheets is transmitted back to the mobile device through wireless network transmission, and displayed on the display screen of the mobile device.
承上所述,依本發明之智能物流資料採集系統,其可具有一或多個下述優點:Based on the above, the intelligent logistics data collection system according to the present invention can have one or more of the following advantages:
(1) 此智能物流資料採集系統能通過影像擷取裝置拍攝板材影像,經由影像分析程序自動產生板材數量,降低人工計數所需成本,提升物流資料採集系統的自動化程度及其便利性。(1) This intelligent logistics data collection system can capture plate images through an image capture device, and automatically generate the number of plates through an image analysis program, reducing the cost of manual counting, and improving the automation and convenience of the logistics data collection system.
(2) 此智能物流資料採集系統能適用於各種不同板材及各種不同數量的板材,並無板材堆疊數量的上限,增加資料採集的彈性及應用範圍。(2) This intelligent logistics data collection system can be applied to various plates and various quantities of plates, and there is no upper limit on the number of plates stacked, which increases the flexibility and application scope of data collection.
(3) 此智能物流資料採集系統能藉由板材計數程序對影像進行處理及分析,避免影像模糊或色彩問題影像判斷結果,提升判斷結果的準確率。(3) This intelligent logistics data collection system can process and analyze the image through the plate counting program, avoid image blurring or color problems in the image judgment result, and improve the accuracy of the judgment result.
為利貴審查委員瞭解本發明之技術特徵、內容與優點及其所能達成之功效,茲將本發明配合附圖,並以實施例之表達形式詳細說明如下,而其中所使用之圖式,其主旨僅為示意及輔助說明書之用,未必為本發明實施後之真實比例與精準配置,故不應就所附之圖式的比例與配置關係解讀、侷限本發明於實際實施上的權利範圍,合先敘明。In order to help the examiners to understand the technical features, content and advantages of the present invention and the effects that can be achieved, the present invention is hereby described in detail with the accompanying drawings and in the form of embodiments as follows. The subject matter is only for illustration and auxiliary description, and is not necessarily the real scale and precise configuration after the implementation of the present invention. Therefore, the ratio and configuration relationship of the attached drawings should not be interpreted or limited to the scope of rights of the present invention in actual implementation. Together first to describe.
本文所使用的所有術語(包括技術和科學術語)具有與本發明所屬技術領域的通常知識者通常理解的含義。將進一步理解的是,諸如在通常使用的字典中定義的那些術語應當被解釋為具有與它們在相關技術和本發明的上下文中的含義一致的含義,並且將不被解釋為理想化的或過度正式的意義,除非本文中明確地如此定義。All terms (including technical and scientific terms) used herein have the meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms such as those defined in commonly used dictionaries should be construed as having meanings consistent with their meanings in the context of the related art and the present invention, and are not to be construed as idealized or excessive Formal meaning unless expressly so defined herein.
請參閱第1圖,其係為本發明實施例之智能物流資料採集系統之方塊圖。如圖所示,智能物流資料採集系統10包含板材輸送裝置11、影像擷取裝置12、影像處理裝置13以及資料輸出裝置14。板材輸送裝置11可包含生產線上的輸送帶或者不同製程產線之間的運送推車。當欲加工的板件運至產線時,可於運送推車上或產線的上料機構處進行檢驗,確認板件數量與製造工單或領料單上的數量是否一致,當產品進行加工後的預定位置及完成加工後要進行移轉時,也都可在定點設置乘載區域,將待測板材111的半成品或成品置於其中,進行板材的計數。在整個生產過程中,待測板材111可以是印刷電路板或是其他材質的板件,這些板件的物流資料,可於設定的位置進行記錄及確認,確實取得生產管理的正確訊息。Please refer to FIG. 1, which is a block diagram of an intelligent logistics data collection system according to an embodiment of the present invention. As shown in the figure, the intelligent logistics
當待測板材11置於乘載區域時,朝向乘載區域的影像擷取裝置12可以拍攝待測板材111的原始影像。影像擷取裝置12可以是產線上固定式的相機,搭配光源拍攝板材照片,再傳送到影像處理裝置13。影像處理裝置13可以連網方式連接於影像擷取裝置12,例如通過網路連線方式傳送原始影像至影像處理裝置13。在另一實施例中,影像擷取裝置12也可為移動裝置,例如智慧型手機、平板電腦或具備攝影鏡頭的手持式裝置,由使用者對著待測板材111拍攝照片後,通過無線網路傳輸方式傳送至影像處理裝置13。When the plate to be tested 11 is placed in the loading area, the
影像處理裝置13包含處理器131及記憶體132,例如電腦、工作站、伺服器等,當接收到原始影像,可將影像資料儲存於記憶體132當中,記憶體132可包含唯讀記憶體、快閃記憶體、磁碟或是雲端資料庫等。處理器131則可包含電腦或伺服器當中的中央處理器、圖像處理器、微處理器等,其可包含多核心的處理單元或者是多個處理單元的組合。處理器131通過各種執行指令來存取記憶體132中的原始影像進行板材計數程序,通過一連串的影像處理與分析程序後,判斷待測板材111當中的板材數量。板材數量的檢測結果,再通過網路傳輸方式,傳送到資料輸出裝置14,由資料輸出裝置14輸出。資料輸出裝置14可以包含影像處理裝置13的顯示器,或者移動裝置的顯示螢幕,通過顯示畫面所呈現的結果,讓操作者能確認板材數量。在其他實施例中,板材數量也可傳送至生產管理系統當中,當板材數量與訂單或工單所記載的數量有所差異時,可發送通知訊號至管理者或監控者,以盡快解決數量不符的問題。至於影像處理裝置13當中執行的板材計數程序,將在以下實施例進一步說明。The image processing device 13 includes a processor 131 and a memory 132, such as a computer, a workstation, a server, etc. When the original image is received, the image data can be stored in the memory 132, and the memory 132 can include a read-only memory, a fast Flash memory, disk or cloud database, etc. The processor 131 may include a central processing unit, an image processor, a microprocessor, etc. in a computer or a server, and may include a multi-core processing unit or a combination of multiple processing units. The processor 131 accesses the original images in the memory 132 through various execution instructions to perform the sheet counting procedure, and after a series of image processing and analysis procedures, determines the number of sheets in the
請參閱第2圖,其係為本發明實施例之影像處理裝置之示意圖。如圖所示,影像處理裝置23接收了相機或移動裝置拍攝的原始影像91,如前述實施例所述,原始影像91儲存於記憶體中,而處理器存取記憶體中的多個控制指令,執行背景分離模組231、特徵增強模組232、區域分割模組233、脊線影像模組234以及板數分析模組235的運算程序以分析原始影像91。Please refer to FIG. 2 , which is a schematic diagram of an image processing apparatus according to an embodiment of the present invention. As shown in the figure, the image processing device 23 receives the
首先背景分離模組231將原始影像91進行切割,背景分離以取得待分析影像92。由於待測板材多以堆疊的方式進行物流傳送,其運送或定位過程需要通過綁帶或夾合的固定件來固定板材位置,在進行檢測時,影像擷取裝置所拍攝的原始影像91可能包含承載區域背景及固定件的影像。因此,背景分離模組231首先將原始影像91中非板材的影像去除,其可通過承載區域標示特徵或者固定件標示特徵來辨別板材與背景的區域,將背景區域去除後,取得待分析影像92。背景分離模組231可通過邊界設定來執行,或者通過人工智慧的智能學習方式,由承式自動判斷區域範圍來進行切割。First, the background separation module 231 cuts the
待分析影像92可輸入至特徵增強模組232,由於原始影像91可能過於模糊而造成判斷上的困難,因此將待分析影像92經由形態學處理將表面平滑化降低噪訊,移除陰影邊界後再藉由色彩空間轉換產生特徵增強影像93。形態學處理包含用一個核心(kernel)遍歷影像,對影像中的像素進行重建,例如擴張(dilate)或侵蝕(erode)的處理,不同核心可具有不同效果,高瘦形的開運算(open)核心能使垂直黑線更聚合,矮胖形的開運算(open)核心可以讓相近的線接在一起。另外,影像的明暗變化也會影響判斷的結果,將影像以RGB色彩模型中色相、飽和度、亮度(HSV)的方式表示,將亮度(V)轉為相同的常數值,再轉回RGB後,就會產生移除陰影的效果。為了避免板材顏色比邊界的脊線還深而造成判斷失誤,還可將RGB影像其轉換成LUV色彩空間,讓電腦能更真實模擬人眼看到的特徵。The image to be analyzed 92 can be input to the feature enhancement module 232. Since the
接著將特徵增強影像93輸入區域分割模組233,將特徵增強影像93進行切割後以訊號雜訊比過濾影像而產生複數個低雜訊影像區段94。將影像以紋理來濾波器萃取強與弱訊號區域,依據堆疊方向切割成的不同區塊,分析不同區段影像噪音密度(noise intensity)差異,以產生多個低雜訊影像區段94。Then, the feature-enhanced image 93 is input into the region segmentation module 233 , and the feature-enhanced image 93 is cut and filtered by the signal-to-noise ratio to generate a plurality of low-noise image segments 94 . The image is filtered to extract strong and weak signal regions by texture, and the difference in noise intensity of the images in different regions is analyzed according to the different blocks cut in the stacking direction, so as to generate a plurality of low-noise image regions 94 .
將這些低雜訊影像區段94輸入脊線影像模組234,將各個低雜訊影像區段94進行影像復原處理及二分類分割處理以得到複數個穩定脊線分布影像區段95。通過點擴散方程式(point spread function) 組成影像復原過濾器(image restoration filter),再經在傅立葉空間濾波以重建影像,推斷脊線間距,並經由脊線間距來進行補線,並且比較兩板材之間空隙與板材之色彩資訊,如有過大的間隙將被濾除,而後產生複數個穩定脊線分布影像區段95。These low-noise image segments 94 are input to the ridgeline image module 234 , and each low-noise image segment 94 is subjected to image restoration processing and two-class segmentation processing to obtain a plurality of stable ridgeline distribution image segments 95 . The image restoration filter is formed by the point spread function, and then filtered in the Fourier space to reconstruct the image, infer the ridge line spacing, and use the ridge line spacing to make up the line, and compare the two plates. The gaps and the color information of the plate, if there are too large gaps, will be filtered out, and then a plurality of stable ridge line distribution image segments 95 will be generated.
將這些穩定脊線分布影像區段95輸入板數分析模組235,統計各個穩定脊線分布影像區段95的脊線數以計算複數個區段板材數量,再統計這些區段板材數量的出現狀況,以當中輸出次數最多的數量作為信置度最佳的板材數量96。計算各個穩定脊線分布影像區段95的脊線數,例如統計有多少像素的RGB值為0,計算零像素的數量作為板材數量96。Input these stable ridge line distribution image segments 95 into the plate number analysis module 235, count the number of ridge lines of each stable ridge line distribution image segment 95 to calculate the number of plates in multiple segments, and then count the occurrence of the number of plates in these segments state, and the number with the highest number of outputs among them is taken as the number of plates with the
經由上述影像處理裝置23執行板材計數程序後,可以檢測待測板材的數量,板材堆疊數量並無板數上限,相較於以厚度估計板數的方式,其預估板數正確性明顯提升,對於產線或物流輸送過程中,板數資料的記錄及追蹤能更有效率且更精準。After the above-mentioned image processing device 23 executes the plate counting procedure, the number of the plates to be tested can be detected. There is no upper limit on the number of plates stacked. Compared with the method of estimating the number of plates by thickness, the accuracy of the estimated number of plates is significantly improved. For the production line or logistics transportation process, the recording and tracking of the board number data can be more efficient and more accurate.
請參閱第3圖,其係為本發明實施例之智能物流資料採集系統之示意圖。如圖所示,智能物流資料採集系統30可由使用者50操作相機32來拍攝待測板材的原始影像91,待測板材的檢測位置,固定等與前述實施例類似,不再重複描述。在其他實施例中,影像擷取裝置也可為產線上固定式的鏡頭。當取得待測板材的原始影像91,則可通過網路通訊方式即時傳送到影像分析的伺服器33,儲存在伺服器33的儲存裝置當中,由伺服器33中的處理器執行板材計數程序,計算待測板材的板材數量96。Please refer to FIG. 3 , which is a schematic diagram of an intelligent logistics data collection system according to an embodiment of the present invention. As shown in the figure, in the intelligent logistics data collection system 30, the
經由運算程序計算的板材數量96,可通過網路傳送至各個產線或檢測點的顯示器341上,於螢幕上顯示待測板材的數量,使用者50可以通過顯示器341檢視板材數量是否符合製造數量或運送數量,若確認相符則可將待測板才放行,經由物流系統送至下一製程產線或進行入庫及出貨的處理。另一方面,板材數量96也可以通過網路通訊網路傳至使用者50的手持裝置342上,通知使用者50板材預估數量,當預估數量與預期板數差異超過預設範圍時,產生警示訊息以通知使用者50,進一步檢視板材數量差異的原因。The number of
以上所述僅為舉例性,而非為限制性者。任何未脫離本發明之精神與範疇,而對其進行之等效修改或變更,均應包含於後附之申請專利範圍中。The above description is exemplary only, not limiting. Any equivalent modifications or changes that do not depart from the spirit and scope of the present invention shall be included in the appended patent application scope.
10:智能物流資料採集系統 11:板材輸送裝置 12:影像擷取裝置 13, 23:影像處理裝置 14:資料輸出裝置 32:相機 33:伺服器 50:使用者 91:原始影像 92:待分析影像 93:特徵增強影像 94:低雜訊影像區段 95:穩定脊線分布影像區段 111:待測板材 131:處理器 132:記憶體 231:背景分離模組 232:特徵增強模組 233:區域分割模組 234:脊線影像模組 235:板數分析模組 341:顯示器 342:手持裝置 10: Intelligent logistics data collection system 11: Plate conveying device 12: Image capture device 13, 23: Image processing device 14: Data output device 32: Camera 33: Server 50: user 91: Original image 92: Image to be analyzed 93: Feature Enhanced Image 94: Low noise image section 95: Image segment of stable ridge distribution 111: Sheet to be tested 131: Processor 132: Memory 231: Background Separation Module 232: Feature Enhancement Module 233: Area segmentation module 234: Ridgeline Image Module 235: Board Count Analysis Module 341: Display 342: Handheld Devices
為使本發明之技術特徵、內容與優點及其所能達成之功效更為顯而易見,茲將本發明配合附圖,並以實施例之表達形式詳細說明如下: 第1圖係為本發明實施例之智能物流資料採集系統之方塊圖。 第2圖係為本發明實施例之影像處理裝置之示意圖。 第3圖係為本發明實施例之智能物流資料採集系統之示意圖。 In order to make the technical features, content and advantages of the present invention and the effects that can be achieved more obvious, the present invention is hereby described in detail as follows in the form of embodiments in conjunction with the accompanying drawings: FIG. 1 is a block diagram of an intelligent logistics data collection system according to an embodiment of the present invention. FIG. 2 is a schematic diagram of an image processing apparatus according to an embodiment of the present invention. FIG. 3 is a schematic diagram of an intelligent logistics data collection system according to an embodiment of the present invention.
10:智能物流資料採集系統 10: Intelligent logistics data collection system
11:板材輸送裝置 11: Plate conveying device
12:影像擷取裝置 12: Image capture device
13:影像處理裝置 13: Image processing device
14:資料輸出裝置 14: Data output device
111:待測板材 111: Sheet to be tested
131:處理器 131: Processor
132:記憶體 132: Memory
Claims (8)
Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
TW110104201A TWI802843B (en) | 2021-02-04 | 2021-02-04 | Intelligent logistics data collection system |
CN202110295439.1A CN114862082A (en) | 2021-02-04 | 2021-03-19 | Intelligent logistics data acquisition system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
TW110104201A TWI802843B (en) | 2021-02-04 | 2021-02-04 | Intelligent logistics data collection system |
Publications (2)
Publication Number | Publication Date |
---|---|
TW202232400A true TW202232400A (en) | 2022-08-16 |
TWI802843B TWI802843B (en) | 2023-05-21 |
Family
ID=82627730
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
TW110104201A TWI802843B (en) | 2021-02-04 | 2021-02-04 | Intelligent logistics data collection system |
Country Status (2)
Country | Link |
---|---|
CN (1) | CN114862082A (en) |
TW (1) | TWI802843B (en) |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN118378994B (en) * | 2024-06-21 | 2024-09-17 | 惠生清洁能源科技集团股份有限公司 | Intelligent storage and taking method for storage stacked aluminum alloy plates |
Family Cites Families (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2005100961A2 (en) * | 2004-04-19 | 2005-10-27 | Phoseon Technology, Inc. | Imaging semiconductor strucutures using solid state illumination |
TW200828176A (en) * | 2006-06-08 | 2008-07-01 | Euclid Discoveries Llc | Apparatus and method for processing video data |
TWM438022U (en) * | 2012-04-26 | 2012-09-21 | Gallant Micro Machining Co Ltd | Detecting apparatus for semiconductor devices |
CN102999451B (en) * | 2012-11-13 | 2015-12-16 | 上海交通大学 | Steel number system and method |
TWI490514B (en) * | 2013-12-17 | 2015-07-01 | Inventec Corp | Detecting system for production line and method thereof |
CN105844327A (en) * | 2016-06-02 | 2016-08-10 | 长春宝钢钢材贸易有限公司 | Image detection-based plate counting device |
CN106600606A (en) * | 2016-12-19 | 2017-04-26 | 上海电气自动化设计研究所有限公司 | Ship painting profile detection method based on image segmentation |
TWM615811U (en) * | 2021-02-04 | 2021-08-21 | 敬鵬工業股份有限公司 | Intelligent logistics data collection system |
-
2021
- 2021-02-04 TW TW110104201A patent/TWI802843B/en active
- 2021-03-19 CN CN202110295439.1A patent/CN114862082A/en active Pending
Also Published As
Publication number | Publication date |
---|---|
TWI802843B (en) | 2023-05-21 |
CN114862082A (en) | 2022-08-05 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US11657599B2 (en) | Method for detecting appearance of six sides of chip multi-layer ceramic capacitor based on artificial intelligence | |
CN110648364B (en) | Multi-dimensional space solid waste visual detection positioning and identification method and system | |
CN105388162B (en) | Raw material silicon chip surface scratch detection method based on machine vision | |
CN104198324B (en) | Computer vision-based method for measuring proportion of cut leaves in cut tobacco | |
CN110618134A (en) | Steel plate surface quality defect detection and rating system and method | |
CN107941808A (en) | 3D printing Forming Quality detecting system and method based on machine vision | |
CN104198325B (en) | Stem ratio measuring method in pipe tobacco based on computer vision | |
TW202242390A (en) | Defect inspection device, defect inspection method, and manufacturing method | |
WO2023168984A1 (en) | Area-array camera-based quality inspection method and system for cathode copper | |
CN110554052A (en) | artificial board surface defect detection method and system | |
CN102901735B (en) | System for carrying out automatic detections upon workpiece defect, cracking, and deformation by using computer | |
CN111062938A (en) | Plate expansion plug detection system and method based on machine learning | |
Zhang et al. | A novel image detection method for internal cracks in corn seeds in an industrial inspection line | |
CN112014407A (en) | Method for detecting surface defects of integrated circuit wafer | |
CN115218790A (en) | Bar inspection method, device and system | |
CN118464928A (en) | A chip quality detection system and chip surface defect detection method based on image processing | |
CN108362693B (en) | Method for detecting qualified rate of insulators on conveyor belt based on image processing | |
TWI802843B (en) | Intelligent logistics data collection system | |
CN114359155A (en) | Film laminating method and system | |
KR102030768B1 (en) | Poultry weight measuring method using image, recording medium and device for performing the method | |
TWM615811U (en) | Intelligent logistics data collection system | |
CN118501177A (en) | Appearance defect detection method and system for formed foil | |
CN117351472A (en) | Tobacco leaf information detection method and device and electronic equipment | |
Labati et al. | Improving OSB wood panel production by vision-based systems for granulometric estimation | |
Dias et al. | Identification of marks on tires using artificial vision for quality control |