Algorithm research on location of bottle mouth and bottom in intelligent empty bottle inspection system

Ma, Sile; Huang, Bin; Wang, Huajie; Guo, Junmei

doi:10.1109/ical.2009.5262809

Cited by 15 publications

(4 citation statements)

References 4 publications

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“…Step 2: Then conveyor belt moving continuously for a fixed time. 3) Step 3: The IR sensors regularly check the bottle. 4) Step 4: when the sensors detect the bottle then the sensors measured the height of bottle.…”

Section: A Steps Of Working 1)mentioning

confidence: 99%

Automatic Variable Size Bottle Filing System

Pandey¹

2019

IJRASET

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The objective of Automatic Bottle Filling System project is to provide easy access to the industries for filling bottles automatically. The project is mainly useful in the cold drinks Manufacturing Company in which drinks is automatically filled in the bottle. Here we use conveyor for whole operation which is controlled with the help of ardiuno microcontroller. In market most of automatic bottle filling systems are having high cost. The target of our project is giving this system to customer in low price. The aim of this project is to design a microcontroller based automatic variable size bottle filling system. In it the bottle moves on the conveyor belt for fixed duration which is already programmed then it sense the level up till which liquid is to be filled in it and then fills it accordingly up to that fixed level.Our project works in two steps. In first step the height of the bottle is measured by an IR sensor and in second step the water is filled up till that height. I.

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Section: A Steps Of Working 1)mentioning

confidence: 99%

Automatic Variable Size Bottle Filing System

Pandey¹

2019

IJRASET

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“…After acquiring the grayscale image we applied edge detection to identify the cap and downsize the image data from grayscale to binary image for the analysis. We use canny edge detector [1,2,3] for edge detection in this research.…”

Section: Second Partmentioning

confidence: 99%

Soda Casket Inspection System by Computer Vision

Orachon¹,

Intani²

2012

AMR

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Referred to the problem a manufacturer always faces that bottles in a casket are missing, caused by the bottles leaning down. Checking the parceling by human causes high risk from the explosion of the lean-down bottles. So this article presents how computer vision is applied to the inspection system. The system used a low-price webcam and image processing method to identify the defection. The process begins with adjusting HSV up before working on edge detection to reduce density of data. Then cross correlation as template matching to define the bottles and check the number of soda bottles. This system can identify 84% of completely loaded casket and 100% of the missing loaded casket.

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“…With reference to the traditional detection of defects in glass bottles, such as the detection of empty beer bottles, empty beverage bottles, etc. [13][14][15][16][17][18][19][20], the following methods are commonly used to detect the bottom of bottles: uses ring light at a specific angle to illuminate the bottom uniformly according to the specific shape of the bottom, and to avoid the interference of the raised pattern of bottom [26,27]. Similarly, the imaging unit images the bottom through the mouth of the bottle.…”

Section: Introductionmentioning

confidence: 99%

“…These methods can achieve uniformed image for bottle bottom inspection with low detection accuracy, or with a small detection field of view. Such as the traditional glass beer bottles and so on [28], the detection accuracy of which is about 3mm×3mm. In addition, for the bottom of the LVP bottle (Fig 1 (C)), the pull ring at the bottom is not at a fixed angle as well as a fixed height, and it is not possible to use the ring light to illuminate the bottom of the bottle evenly.…”

Section: Introductionmentioning

confidence: 99%

Machine vision model for detection of foreign substances at the bottom of empty large volume parenteral

Yuan,

Li,

Tang

et al. 2024

PLoS ONE

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Empty large volume parenteral (LVP) bottle has irregular shape and narrow opening, and its detection accuracy of the foreign substances at the bottom is higher than that of ordinary packaging bottles. The current traditional detection method for the bottom of LVP bottles is to directly use manual visual inspection, which involves high labor intensity and is prone to visual fatigue and quality fluctuations, resulting in limited applicability for the detection of the bottom of LVP bottles. A geometric constraint-based detection model (GCBDM) has been proposed, which combines the imaging model and the shape characteristics of the bottle to construct a constraint model of the imaging parameters, according to the detection accuracy and the field of view. Then, the imaging model is designed and optimized for the detection. Further, the generalized GCBDM has been adopted to different bottle bottom detection scenarios, such as cough syrup and capsule medicine bottles by changing the target parameters of the model. The GCBDM, on the one hand, can avoid the information at the bottom being blocked by the narrow opening in the imaging optical path. On the other hand, by calculating the maximum position deviation between the center of visual inspection and the center of the bottom, it can provide the basis for the accuracy design of the transmission mechanism in the inspection, thus further ensuring the stability of the detection.

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Algorithm research on location of bottle mouth and bottom in intelligent empty bottle inspection system

Cited by 15 publications

References 4 publications

Automatic Variable Size Bottle Filing System

Automatic Variable Size Bottle Filing System

Soda Casket Inspection System by Computer Vision

Machine vision model for detection of foreign substances at the bottom of empty large volume parenteral

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