Method for detecting dirt on central region of bottom of beer bottle

Abstract

The invention relates to a method for detecting dirt on a central region of a bottom of a beer bottle. The method comprises the following steps of: positioning a central circle region of an acquired bottle bottom picture; treating the positioned region by using a template; evaluating connected domains after template treatment; calculating the area of each connected domain; judging the magnitude of the area and comparing the area with a threshold value to determine the existence of disturbance or possible dirt; evaluating the lengths and widths of rectangles of connected regions which can be framed by a smallest rectangle and have the same mark number for an image from which the disturbance is removed; comparing the ratio of the length and the width; determining that the dirt, namely, linear dirt, exists if the ratio is more than or less than a fixed value; and otherwise, calculating the area of the rectangle and determining that the dirt exists if the area of the rectangle is more than a certain threshold value, otherwise determining that the disturbance exists. The detection method provided by the invention has the characteristics of high speed and high accuracy and is suitable for the conventional domestic beer bottle detection devices.

Description

Technical field: [0001] The invention relates to the technical field of image processing, in particular to a method for detecting dirt in the central area of ​​the bottom of a beer bottle. The method is also suitable for detecting dirt in transparent objects such as plastic bottles and glass bottles. Background technique: [0002] At present, many beer manufacturers adopt the strategy of recycling beer bottles in order to save costs. But recycled beer bottles may have many defects due to contamination or damage. Therefore, beer bottles must be tested before bottling to eliminate defective beer bottles. In addition, with the increasingly intensified market competition and the gradual enhancement of consumers' awareness of rights protection, beer bottle manufacturers are paying more and more attention to product quality. [0003] At present, the detection of beer bottles in China is mainly based on the visual detection of artificial light. However, the detection efficiency ...

AI Technical Summary

Problems solved by technology

However, at present, most of the testing machines used by domestic beer bottle manufacturers are imported, which are expensive, and generally small and medium-sized enterprises cannot afford to buy them. In addition, due to factors such as bottle size, color, and national conditions, foreign testing equipment is not fully applicable. domestic situation

On the domestic beer production line, the recycled beer bottles still face the following problems after cleaning: (1) The mouth of the bottle is damaged, which will lead to the failure of the beer bottle packaging or the potential safety hazards in the packaging, resulting in the appearance of defective products, which seriously affects the quality of beer. quality

(2) The bottom of the bottle body is damaged, which will cause the beer bottle to have a hidden danger of explosion after pressurization

(3) There are foreign objects on the bottle body and the inner wall of the bottom of the bottle

However, this method can completely detect obvious defects, but it is powerless for the interference caused by the unevenness of the beer bottle itself or some small dirt and crack interference, such as the uneven thickness of the bottom glass of the beer bottle. The gray values ​​of the two symmetrical sub-blocks are not consistent, and the above algorithm will detect the bottle as unqualified, resulting in false detection; another example is for fine dirt such as hair strands or linear dirt such as cracks in the beer bottle itself. , the changes in the gray level caused by these existing dirt are very small, and the above methods are powerless to it

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