Image acquisition control method based on bar code reading

Abstract

The invention belongs to the technical field of image acquisition, and provides an image acquisition control method based on bar code reading, which comprises the following steps: starting a scanning session through triggering; during the scanning session, the image sensor circularly executes pulse type acquisition batches, and each batch comprises N frames of image acquisition; in a processing period between two adjacent acquisition batches, the light supplementing unit continuously works in a visual maintenance mode; performing quality analysis on the acquired images in each acquisition batch frame by frame, and if the current frame image meets a decoding condition, sending the current frame image to decode; and if the decoding is successful, immediately terminating the acquisition of the subsequent frame image and terminating the scanning session. By setting a cyclic pulse type acquisition batch and a processing period, the flicker condition of human eye sense can be eliminated, the user experience is improved, and meanwhile, the power consumption of the whole machine is reduced to the maximum extent.

Description

Technical Field

[0001] This invention relates to the field of image acquisition technology, and in particular to an image acquisition control method based on barcode reading. Background Technology

[0002] Current image scanning devices face a fundamental design dilemma in their pursuit of high decoding rates and fast response times for a superior user experience. To ensure flicker-free, stable illumination during user operation, mainstream high-performance solutions typically operate the image sensor and synchronized illumination at a high frame rate (e.g., 60fps). In this mode, because the illumination flicker is far higher than the human eye's persistence of vision threshold, the user perceives a continuous light source, resulting in a smooth experience. However, this strategy comes at the cost of significant and continuous power consumption. For the vast majority of the time the user is attempting to decode the target or system, the image frames acquired by the front end are not effectively utilized; instead, they are discarded or overwritten by the back-end processing system due to insufficient processing time. For battery-powered portable devices, this "full-speed idling" power waste is a core bottleneck limiting their battery life.

[0003] To address power consumption issues, the industry has proposed the concept of "on-demand frame acquisition," which means initiating image acquisition only when needed. The simplest implementation is "snapshot mode," which involves a single trigger and a single acquisition. While this mode consumes extremely low power, it also introduces a serious problem: due to the discontinuous nature of the acquisition task, the illumination of the supplementary light becomes irregular and low-frequency flickering. This flickering is particularly noticeable when the user repeatedly attempts to decode, greatly impairing visual comfort and the smoothness of operation. Summary of the Invention

[0004] This invention provides an image acquisition control method based on barcode reading, which solves the problem of huge and unnecessary power consumption caused by the continuous high-speed image acquisition strategy adopted by barcode scanning devices to ensure a flicker-free experience in the prior art.

[0005] This invention provides an image acquisition and control method based on barcode reading, comprising:

[0006] A scanning session is initiated via a trigger;

[0007] During a scanning session, the image sensor cyclically performs pulsed acquisition batches, each batch containing N frames of image acquisition;

[0008] During the processing period between two adjacent acquisition batches, the supplemental lighting unit continues to operate in vision maintenance mode.

[0009] For each batch of images acquired, perform quality analysis frame by frame. If the current frame meets the decoding conditions, send it for decoding.

[0010] If decoding is successful, the acquisition of subsequent frame images will be terminated immediately and the current scanning session will end.

[0011] According to the image acquisition control method based on barcode reading provided by the present invention, the supplementary lighting unit works continuously in synchronous exposure mode within each acquisition batch.

[0012] According to the image acquisition control method based on barcode reading provided by the present invention, if the last frame of the current acquisition batch cannot be successfully decoded, the current processing period ends and the next acquisition batch begins.

[0013] According to the image acquisition control method based on barcode reading provided by the present invention, if multiple batches of images cannot be successfully decoded, a classic computer vision algorithm is used to decode the images in the last batch frame by frame.

[0014] According to the image acquisition and control method based on barcode reading provided by the present invention, the situations in which decoding cannot be successfully performed include those in which the decoding conditions are not met or the decoding fails.

[0015] According to the image acquisition control method based on barcode reading provided by the present invention, in each acquisition batch, the image sensor acquires images at a frame rate of 60-70fps and a resolution of 1280*800.

[0016] According to the image acquisition control method based on barcode reading provided by the present invention, a lightweight model is used to perform quality analysis on each frame of the acquired image to obtain image quality parameters including at least barcode confidence, sharpness score, exposure score and structural integrity score; when the barcode confidence is greater than 0.9, the sharpness score is greater than 0.8, the exposure score is greater than 0.7 and the structural integrity score is greater than 0.9, the decoding condition is met.

[0017] According to the image acquisition control method based on barcode reading provided by the present invention, if the current frame image does not meet the decoding conditions, the frame image is discarded.

[0018] According to the present invention, an image acquisition control method based on barcode reading is provided, wherein the vision maintenance mode includes supplementary lighting with a current of 600 mA and a frequency of 60 Hz.

[0019] According to the present invention, an image acquisition control method based on barcode reading is provided, wherein the synchronous exposure mode includes supplementary lighting with a current of 900 mA and a frequency of 60-70 Hz.

[0020] The image acquisition control method based on barcode reading provided by this invention cyclically executes pulsed acquisition batches, while setting a processing period between two adjacent acquisition batches. The supplementary lighting unit works continuously in synchronous exposure mode within each acquisition batch and in visual maintenance mode within each processing period. This can eliminate flickering perceived by the human eye, improve the user experience, and at the same time, minimize the overall power consumption. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0022] Figure 1 This is one of the flowcharts illustrating the image acquisition and control method based on barcode reading provided by the present invention;

[0023] Figure 2 This is the second flowchart of the image acquisition and control method based on barcode reading provided by the present invention;

[0024] Figure 3 This is a timing diagram of the image sensor and the illumination unit;

[0025] Figure 4 This is a schematic diagram of the scanning device of the present invention. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0027] The following is combined Figures 1-4 This invention describes an image acquisition and control method based on barcode reading. This method is applicable to barcode scanning devices (including barcode scanners, PDAs, mobile phones, tablets, etc.) equipped with an AI model. The scanning device has an image sensor, a supplementary lighting unit, a decoding unit (decoding engine), a storage unit, and a main control unit. The AI ​​model is configured within the main control unit and is used to perform quality analysis on the images acquired by the image sensor. By introducing the AI ​​model, the method can determine whether to decode the current frame image based on the quality analysis results. Compared to the traditional method of decoding frame by frame using classic computer vision algorithms, this method offers greater flexibility, faster decoding efficiency, and a higher decoding success rate.

[0028] The image acquisition and control method based on barcode reading in this application includes:

[0029] The scanning session is initiated by triggering; during non-scanning sessions, the scanning device is in a sleep state. After being triggered by human intervention or a signal, it enters the working state from the sleep state and begins scanning.

[0030] During a scanning session, the image sensor cyclically executes pulsed acquisition batches, each batch containing N frames of image acquisition; where N is equal to 3 or 4, or other values ​​may be used as needed; within each acquisition batch, the supplementary lighting unit continuously operates in synchronous exposure mode to provide supplementary lighting while the image sensor acquires images, and to ensure that the user perceives a stable illumination within this brief acquisition window.

[0031] During the processing period between two adjacent acquisition batches, the supplementary lighting unit continues to operate in visual maintenance mode. In visual maintenance mode, the brightness of the supplementary lighting unit is not significantly different from that in synchronous exposure mode, and neither mode causes flickering to the human eye. During the processing period, a "background light" that is imperceptible to the human eye seamlessly fills the dark field that would otherwise be generated "on demand", thereby maintaining visual continuity throughout the session and eliminating flickering.

[0032] For each batch of images acquired, perform quality analysis frame by frame. If the current frame meets the decoding conditions, send it for decoding.

[0033] If decoding is successful, the acquisition of subsequent frames is immediately terminated and the scanning session ends; the scanning device enters sleep mode, waiting for the next trigger. Within an acquisition batch, image quality is evaluated in real time using a rolling pipeline approach of "acquire one frame, analyze one frame". Once a high-quality frame is found, it is immediately sent for successful decoding (images that have undergone quality analysis and meet the decoding conditions have a high success rate when decoding), preemptively terminating subsequent unnecessary acquisitions, minimizing latency and power consumption.

[0034] In this embodiment, if the last frame of the current acquisition batch cannot be successfully decoded, the current processing period ends and the next acquisition batch begins.

[0035] If multiple batches of images fail to decode successfully, a classic computer vision algorithm is used to decode the images in the last batch frame by frame. Similarly, if the current frame in the last batch is successfully decoded, the decoding of subsequent frames is terminated. The quality analysis used in the aforementioned steps is based on AI positioning algorithms. When the core AI positioning algorithm fails consecutively, it automatically switches to or uses classic computer vision algorithms in parallel for supplementary searching, serving as a "Plan B" to ensure robustness. This approach can handle complex real-world application scenarios, achieving a comprehensive improvement in system performance and reliability, and further enhancing the efficiency, real-time performance, and robustness of the barcode scanning device.

[0036] The number of acquisition batches here can be set to three or four. That is, there can be a maximum of three or four acquisition batches in each scanning session. A processing period is set between two adjacent acquisition batches. The existence of the processing period is to reserve sufficient time for the AI ​​model to perform quality analysis on the acquired images and for the decoding unit to decode the images that meet the decoding conditions.

[0037] It's important to understand that the duration of each processing cycle is not fixed because the image quality varies from frame to frame. Therefore, the time the AI ​​model takes to analyze each frame also varies. However, the time difference for decoding images that meet the decoding criteria is not significant (because meeting the decoding criteria indicates good image quality, and the decoding time is roughly the same). Figure 3 As shown, time period t1 is a data collection batch, and theoretically, the duration of t1 is fixed; time period t2 is the processing period, and its duration is not fixed, and will change depending on the length of successful decoding or analysis.

[0038] It can be further confirmed that the time taken for the AI ​​model to analyze each frame of the image is much greater than 1 / 60 of a second, meaning that the number of times it can analyze the image per second is much less than 60. The frame rate of the image sensor can be customized. Generally speaking, the flashing frequency of the supplementary lighting unit will be synchronized with the frame rate of the image sensor. If the frame rate of the image sensor is low, the flashing frequency of the supplementary lighting unit will also be lower. When it is lower than the flashing frequency that the human eye can perceive, the human eye will perceive flicker.

[0039] Furthermore, during barcode reading, the image sensor's image acquisition (also known as image exposure) accounts for the largest share of the overall power consumption, far exceeding the power consumption of the illumination unit. If the process is carried out in the order of acquiring one frame, analyzing one frame, and decoding one frame, power consumption can be reduced to the minimum. However, since the duration of analyzing a frame image will exceed 1 / 60 of a second, the flicker frequency of the illumination unit must be lower than 60Hz, which will cause flickering in the human eye and result in a poor user experience. On the other hand, if images are continuously acquired at a high frame rate and the illumination is flickered at a high frequency, the flickering perceived by the human eye can be eliminated, but this will result in a significant increase in power consumption.

[0040] Therefore, this application completely eliminates the flicker problem through an innovative supplementary lighting timing logic, providing users with a smooth and comfortable visual experience; at the same time, it can significantly reduce power consumption.

[0041] In this application, the situations in which decoding cannot be successfully performed include those in which the decoding conditions are not met or decoding fails.

[0042] In this application, a lightweight model (i.e., an AI model, which can employ a quality assessment network based on ResNet or EfficientNet backbone to output more refined and multi-dimensional quality parameters) is used to perform quality analysis on each frame of the acquired images, obtaining image quality parameters including at least barcode confidence, sharpness score (measuring edge sharpness), exposure score (determining whether there is overexposure, underexposure, or uneven lighting), and structural integrity score (evaluating the integrity and unobstructedness of key barcode structures such as positioning points, bars, and spaces). The decoding condition is met when the barcode confidence is greater than 0.9, the sharpness score is greater than 0.8, the exposure score is greater than 0.7, and the structural integrity score is greater than 0.9.

[0043] Specifically, within a batch other than the last acquisition, if the current frame does not meet the decoding conditions, the frame is discarded.

[0044] Specifically, to achieve the goal of eliminating flicker perceived by the human eye as described above, within each acquisition batch, the image sensor acquires images at a frame rate of 60-70fps and a resolution of 1280*800. The synchronous exposure mode includes supplementary lighting at a frequency of 60-70Hz, synchronizing with the image sensor's acquisition frame rate using a current of 900 mA. The vision maintenance mode includes supplementary lighting at a frequency of 60Hz and a current of 600 mA. That is, when the frequency of the supplementary lighting unit exceeds 60Hz, the human eye cannot perceive flicker; therefore, in the vision maintenance mode, the lowest frequency can be used to reduce power consumption. Secondly, the difference in brightness between the 600 mA and 900 mA currents is not significant to the naked eye; therefore, the lowest current intensity is also used to reduce power consumption.

[0045] Of course, within each acquisition batch, the image sensor and the supplementary lighting unit can operate at a higher frequency. However, considering the time consumed by the AI ​​model in the image quality analysis and decoding stages, and to avoid the image sensor acquiring too many frames (assuming that 3 frames are acquired quickly and decoded successfully in the 2nd or even 1st frame, the extra image acquisition will cause a lot of power consumption), the scanning device will operate with the lowest possible power consumption while ensuring the elimination of human visual flicker.

[0046] In summary, this application has the following beneficial effects:

[0047] 1. Fundamental reduction in power consumption: By shifting from "continuous acquisition" to "intelligent on-demand frame acquisition", the system only activates high-power front-end acquisition and supplemental lighting when absolutely necessary, fundamentally solving the problem of excessive power consumption and greatly improving the battery life of portable devices.

[0048] 2. Revolutionary user experience: The original "dual-mode supplementary lighting" mechanism, especially the application of "visual maintenance mode", perfectly solves the flickering problem that inevitably occurs in the "on-demand frame capture" mode, allowing users to enjoy the long battery life brought by low power consumption while obtaining a smooth visual experience with no flicker and no interruption comparable to high-end continuous acquisition devices.

[0049] 3. Extremely high acquisition efficiency and success rate: A series of intelligent decision-making mechanisms ensure that every "frame capture on demand" is as efficient and accurate as possible, avoiding blind and ineffective acquisition and decoding, thereby improving the first scan success rate and overall performance.

[0050] 4. Comprehensive system robustness and reliability: The AI ​​failure defense mechanism (using classic computer vision for decoding) ensures the robustness of the algorithm layer, enabling the product to reach industrial-grade reliability standards.

[0051] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An image acquisition and control method based on barcode reading, characterized in that, include: A scanning session is initiated via a trigger; During a scanning session, the image sensor cyclically performs pulsed acquisition batches, each batch containing N frames of image acquisition; During the processing period between two adjacent acquisition batches, the supplemental lighting unit continues to operate in vision maintenance mode. For each batch of images acquired, perform quality analysis frame by frame. If the current frame meets the decoding conditions, send it for decoding. If decoding is successful, the acquisition of subsequent frame images will be terminated immediately and the current scanning session will end.

2. The image acquisition and control method based on barcode reading according to claim 1, characterized in that, Within each acquisition batch, the supplemental lighting unit operates continuously in synchronous exposure mode.

3. The image acquisition and control method based on barcode reading according to claim 1, characterized in that, If the last frame of the current batch cannot be successfully decoded, the current processing period ends and the next batch begins.

4. The image acquisition and control method based on barcode reading according to claim 3, characterized in that, If images from multiple acquisition batches cannot be successfully decoded, then a classic computer vision algorithm is used to decode the images in the last acquisition batch frame by frame.

5. The image acquisition and control method based on barcode reading according to claim 4, characterized in that, Unsuccessful decoding may occur if the decoding conditions are not met or if decoding fails.

6. The image acquisition and control method based on barcode reading according to claim 1, characterized in that, Within each acquisition batch, the image sensor acquires images at a frame rate of 60-70fps and a resolution of 1280*800.

7. The image acquisition and control method based on barcode reading according to claim 1, characterized in that, A lightweight model is used to perform quality analysis on each frame of the acquired images to obtain image quality parameters including at least barcode confidence, sharpness score, exposure score, and structural integrity score. The decoding condition is met when the barcode confidence is greater than 0.9, the sharpness score is greater than 0.8, the exposure score is greater than 0.7, and the structural integrity score is greater than 0.

9.

8. The image acquisition and control method based on barcode reading according to claim 1, characterized in that, If the current frame does not meet the decoding conditions, the frame is discarded.

9. The image acquisition and control method based on barcode reading according to claim 1, characterized in that, The vision maintenance mode includes supplemental lighting at a current of 600 mA and a frequency of 60 Hz.

10. The image acquisition and control method based on barcode reading according to claim 2, characterized in that, The synchronous exposure mode includes supplemental lighting with a current of 900 mA and a frequency of 60-70 Hz.

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