Brand VI element-based propaganda picture rapid matching method

Abstract

The invention discloses a propaganda picture rapid matching method based on brand VI elements, and particularly relates to the field of brand visual image management, and the method comprises the following specific steps: 1, preprocessing the VI elements; 2, analyzing the demand in real time; step 3, dynamic semantic matching; step 4, conflict pre-detection optimization; step 5, carrying out real-time multi-modal verification; step 6, updating the incremental atlas; step 7, deriving and outputting in batches; and 8, performing interactive correction. According to the method, second-level intelligent generation of brand propaganda pictures can be realized, relying on a three-level priority channel and a conflict pre-detection mechanism, the matching effect is good, the brand violation rate is reduced, one-key generation of multiple cross-medium adaptive versions is supported, triple breakthrough of design quality, efficiency and compliance is synchronously realized, an intelligent closed loop of brand visual management is constructed, and the brand propaganda effect is improved. According to the matching verification method, rapid matching, verification and generation of a version adaptive to multiple platform sizes are achieved, and user preference effects can be adjusted and retained according to user feedback.

Description

Technical Field

[0001] The present invention relates to the field of brand visual image management, and more specifically, to a method for quickly matching promotional images based on brand VI elements. Background Art

[0002] In today's era of highly developed digitalization and visual communication, the unity and recognizability of a brand image are crucial to a company's market competitiveness. As a crucial component of brand strategy, the brand's visual identity (VI) system, through a series of carefully designed visual elements such as the logo, standard colors, standard fonts, auxiliary graphics, and symbolic patterns, constructs a brand's unique visual language, ensuring a consistent visual image across various communication channels, thereby deepening consumers' recognition and memory of the brand. With the rise of multi-channel marketing, including social media, digital advertising, and offline events, brands need to convey their visual messages efficiently and accurately in a short period of time to attract the attention of their target audiences. However, faced with the massive demand for promotional materials, how to quickly and accurately match brand VI elements to various promotional images has become a major challenge for brand management and marketing teams.

[0003] In the field of brand visual identity (VI) management, efficient production of promotional images has always been a core requirement of corporate marketing. Traditional design processes rely heavily on manual operations: designers must manually search brand manuals, screen VI elements, assemble layouts, and repeatedly verify compliance. The average time required for a single draft is long, and there are the following industry pain points:

[0004] 1. Design efficiency bottleneck: Manual search of VI element libraries takes over 30% of the time, and cross-departmental collaboration is prone to version confusion;

[0005] 2. Brand compliance risk: According to statistics, 38% of companies have suffered brand damage due to the illegal use of non-standard fonts / colors in design drafts;

[0006] 3. Cross-media adaptation dilemma: The same design needs to be repeatedly adjusted for different media, and the creation of derivative versions takes up 60% of the total process time;

[0007] 4. Intelligence gap: Existing tools (such as the Adobe template library) only provide static material management and lack the ability to understand scene semantics and dynamically match scenes. They cannot meet the high-frequency, multi-scenario marketing needs of industries such as fast-moving consumer goods and e-commerce. Summary of the Invention

[0008] In order to overcome the above-mentioned defects of the prior art, the present invention provides a method for quickly matching promotional images based on brand VI elements.

[0009] To achieve the above-mentioned purpose, the present invention provides the following technical solution: a method for quickly matching promotional images based on brand VI elements, the specific steps of which are as follows:

[0010] Step 1: VI element preprocessing: Structure the brand standard element library, including metadata and semantic tags for colors, graphics, and fonts;

[0011] Step 2: Real-time demand analysis: Extract scenario keywords and emotional tendencies from input demands through natural language processing;

[0012] Step 3: Dynamic semantic matching: Associating VI elements with scenario labels based on the knowledge graph to generate a prioritized set of combination solutions;

[0013] Step 4: Conflict Pre-check Optimization: Automatically detect and eliminate visual conflicts between elements and output optimization solutions;

[0014] Step 5: Real-time multimodal verification: Simultaneously verify the design draft’s brand compliance and cross-media adaptability;

[0015] Step 6: Incremental graph update: Dynamically strengthen the high-frequency element association path based on user selection data;

[0016] Step 7. Batch derivative output: Generate derivative versions that adapt to multiple platform sizes with one click;

[0017] Step 8. Interactive correction: locally adjust elements based on user feedback and keep the modification track;

[0018] Step 9: Intelligent memory output.

[0019] As a further improvement to the technical solution of the present invention, the step 3 dynamic semantic matching specifically includes establishing three-layer priority channels and combining and sorting them according to channel weights, with a response time of ≤3 seconds, wherein the three-layer priority channels include:

[0020] (1) Level 1 channel: mandatory brand elements (logo, primary color);

[0021] (2) Secondary channel: scene-related elements (festival graphics, product icons);

[0022] (3) Level 3 channel: historically preferred elements.

[0023] As a further improvement to the technical solution of the present invention, the conflict pre-check in step 4 includes:

[0024] (1) Color vibration warning: triggers an alarm when complementary colors are adjacent and the area ratio is greater than 1:3;

[0025] (2) Layout density control: ensure that the negative space ratio is ≥25%;

[0026] (3) Font hierarchy conflict detection: Headline font size is no more than 300% of body font size.

[0027] As a further improvement of the technical scheme of the application, the step five real-time multi-modal verification specifically includes:

[0028] (1) Brand compliance verification: Real-time check of logo safety margin, main color proportion, and font authorization status;

[0029] (2) Media adaptation verification: Automatically adjust resolution and color mode according to output medium.

[0030] As a further improvement of the technical scheme of the application, the step six incremental graph update specifically updates the knowledge graph by the following way:

[0031] (1) Record the element combination path of the user's final selected scheme;

[0032] (2) Strengthen the correlation weight of the selected path and weaken the unselected path;

[0033] (3) Trigger version snapshot backup when the weight changes more than 30%.

[0034] As a further improvement of the technical scheme of the application, the step seven batch derivative output specifically includes automatically deriving size versions and application style migration after the main manuscript is generated to maintain multi-version visual consistency, wherein the following size versions are automatically derived after the main manuscript is generated: social media version (1080x1080 pixels), printed poster version (A3 / A4 resolution 300dpi)

[0035] and mobile vertical version (9:16 ratio).

[0036] As a further improvement of the technical scheme of the application, the step eight interactive correction implementation specifically includes:

[0037] S1, mark the editable element hot area in the preview interface;

[0038] S2, automatically lock the relative proportion of associated elements when dragging and modifying;

[0039] S3, record the modification history and generate a traceable decision tree.

[0040] As a further improvement of the technical scheme of the application, the step nine intelligent memory output specifically includes the following contents:

[0041] (1) Establish a personalized element preference profile for the user;

[0042] (2) When similar scenarios are detected, preferentially call the historical preferred combination;

[0043] (3) Provide new and old scheme comparison view to assist decision-making.

[0044] Advantages of the present application:

[0045] The present application designs a brand VI element-based promotion picture fast matching method, realizes brand promotion picture second-level intelligent generation, greatly improves the efficiency compared with the traditional design process, relies on three-level priority channel and conflict pre-check mechanism, and has good matching effect, greatly increases the first draft passing rate, and reduces the brand violation rate; combined with incremental learning and multi-platform style migration technology, the system adaptively optimizes the matching accuracy, supports one-key generation of various cross-media adaptation versions, simultaneously realizes the threefold breakthrough of design quality, efficiency and compliance, constructs the intelligent closed loop of brand visual management, and achieves the matching verification method of fast matching, inspection, generation of adaptive multi-platform size version, adjustment according to user feedback and retention of user preference effect. BRIEF DESCRIPTION OF DRAWINGS

[0046] Figure 1 The method flowchart of the present application. DETAILED DESCRIPTION

[0047] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0048] As shown in the brand VI element-based promotion picture fast matching method shown in the accompanying drawings, Figure 1 The specific steps are as follows:

[0049] Step 1, VI element preprocessing: structurally store the brand standard element library, including the metadata and semantic tags of color, graphics and font;

[0050] Step 2, demand instant analysis: extract the scene keywords and emotional tendency in the input demand through natural language processing;

[0051] Step 3, dynamic semantic matching: associate VI elements and scene tags based on knowledge graph to generate a combination scheme set with priority order;

[0052] Step 4, conflict pre-check optimization: automatically detect and eliminate visual conflicts between elements, and output an optimized scheme;

[0053] Step 5, real-time multi-modal verification: simultaneously verify the brand compliance and cross-media adaptability of the design draft;

[0054] Step 6: Incremental graph update: Dynamically strengthen the high-frequency element association path based on user selection data;

[0055] Step 7. Batch derivative output: Generate derivative versions that adapt to multiple platform sizes with one click;

[0056] Step 8. Interactive correction: locally adjust elements based on user feedback and keep the modification track;

[0057] Step 9: Intelligent memory output.

[0058] Step 3, dynamic semantic matching, specifically includes establishing three-tier priority channels and combining and sorting them by channel weights, with a response time of ≤ 3 seconds. The three-tier priority channels include:

[0059] (1) Level 1 channel: mandatory brand elements (logo, primary color);

[0060] (2) Secondary channel: scene-related elements (festival graphics, product icons);

[0061] (3) Level 3 channel: historically preferred elements.

[0062] The conflict pre-check in step 4 includes:

[0063] (1) Color vibration warning: triggers an alarm when complementary colors are adjacent and the area ratio is greater than 1:3;

[0064] (2) Layout density control: ensure that the negative space ratio is ≥25%;

[0065] (3) Font level conflict detection: The title font size shall not exceed 300% of the main text size.

[0066] Among them, step 5 real-time multimodal verification specifically includes:

[0067] (1) Brand compliance verification: Real-time check of logo safety margins, primary color ratio, and font authorization status;

[0068] (2) Media adaptation verification: Automatically adjust the resolution and color mode according to the output medium.

[0069] Among them, step 6 incremental graph update specifically updates the knowledge graph in the following way:

[0070] (1) Record the element combination path of the user's final choice;

[0071] (2) Strengthen the association weight of the selected path and weaken the unselected path;

[0072] (3) When the weight change exceeds 30%, a version snapshot backup is triggered.

[0073] Among them, step seven batch derivative output specifically includes automatically deriving size versions after the master draft is generated and applying style migration to maintain visual consistency among multiple versions. Among them, the following size versions are automatically derived after the master draft is generated: social media version (1080x1080 pixels), printed poster version (A3 / A4 resolution 300dpi) and mobile vertical version (9:16 ratio).

[0074] The interactive correction implementation of step eight is specifically as follows:

[0075] S1. Mark the editable element hotspot on the preview interface;

[0076] S2. Automatically lock the relative proportions of related elements when dragging and modifying;

[0077] S3. Record the modification history and generate a traceable decision tree.

[0078] Among them, step nine, intelligent memory output, specifically includes the following contents:

[0079] (1) Establish personalized element preference profiles for users;

[0080] (2) When similar scenarios are detected, the historical preferred combination is preferentially called;

[0081] (3) Provide a comparison view of new and old solutions to assist in decision-making.

[0082] In summary, the present invention designs a method for quickly matching promotional images based on brand VI elements. The specific steps are as follows:

[0083] First, VI elements are pre-processed to structure the brand standard element library, including metadata and semantic tags for colors, graphics, and fonts. Second, demand-driven analysis is performed, extracting scenario keywords and sentiment from the input requirements through natural language processing. Then, based on dynamic semantic matching, VI elements and scenario tags are associated with the knowledge graph to generate a prioritized set of combination solutions for matching. This includes establishing three-tiered priority channels and ranking combinations by channel weight, with a response time of ≤3 seconds. Conflict pre-check optimization is then performed to automatically detect and eliminate visual conflicts between elements and output an optimized solution. Conflict pre-check includes color vibration warnings, layout density control, and font-level conflict detection. Real-time multimodal validation is then performed to simultaneously verify the brand compliance and cross-media adaptability of the design draft. Furthermore, high-frequency element association paths are dynamically strengthened based on user selection data for incremental graph updates. Derivative versions adapted for multiple platform sizes are then generated with one click. Based on user feedback, elements are locally adjusted, retaining modification traces for interactive correction. Finally, a personalized element preference profile is created for the user. When similar scenarios are detected, historically preferred combinations are prioritized, providing a comparison view of new and old solutions to aid decision-making.

[0084] According to the above method design, combined with the traditional matching method comparison, the matching speed comparison data table is as follows:

[0085] Link Traditional methods are time-consuming This solution takes time Requirements Analysis 3-5 minutes 0.5-1 second Element Matching 2-8 minutes 2-3 seconds Conflict detection and repair 10-30 minutes Completed in real time Multi-platform output 30-60 minutes 10-15 seconds Total time for the whole process 45-103 minutes 12.5-19 seconds

[0086] In summary, the present invention designs a fast matching method for promotional images based on brand VI elements, which realizes the intelligent generation of brand promotional images in seconds, and greatly improves the efficiency compared with the traditional design process; relying on the three-level priority channel and conflict pre-check mechanism, the matching effect is good, the first draft pass rate is greatly increased, and the brand violation rate is reduced; combining incremental learning and multi-platform style transfer technology, the system adaptively optimizes the matching accuracy, and supports one-click generation of multiple cross-media adaptation versions, and simultaneously achieves a triple breakthrough in design quality, efficiency and compliance, and builds an intelligent closed loop of brand visual management, achieving a matching verification method that can quickly match, test, and generate versions adapted to multiple platform sizes, can be adjusted according to user feedback, and retains user preferences.

[0087] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for quickly matching promotional images based on brand VI elements, characterized in that: The specific steps are as follows: Step 1: VI element preprocessing: Structure the brand standard element library, including metadata and semantic tags for colors, graphics, and fonts; Step 2: Real-time demand analysis: Extract scenario keywords and emotional tendencies from input demands through natural language processing; Step 3: Dynamic semantic matching: Associating VI elements with scenario labels based on the knowledge graph to generate a prioritized set of combination solutions; Step 4: Conflict Pre-check Optimization: Automatically detect and eliminate visual conflicts between elements and output optimization solutions; Step 5: Real-time multimodal verification: Simultaneously verify the design draft’s brand compliance and cross-media adaptability; Step 6: Incremental graph update: Dynamically strengthen the high-frequency element association path based on user selection data; Step 7. Batch derivative output: Generate derivative versions that adapt to multiple platform sizes with one click; Step 8. Interactive correction: locally adjust elements based on user feedback and keep the modification track; Step 9: Intelligent memory output.

2. The method for quickly matching promotional images based on brand VI elements according to claim 1, characterized in that: The step 3 dynamic semantic matching specifically includes establishing three-layer priority channels and combining and sorting them according to channel weights, with a response time of ≤ 3 seconds. The three-layer priority channels include: (1) Level 1 channel: mandatory brand elements (logo, primary color); (2) Secondary channel: scene-related elements (festival graphics, product icons); (3) Level 3 channel: historically preferred elements.

3. The method for quickly matching promotional images based on brand VI elements according to claim 1, characterized in that: The conflict pre-check in step 4 includes: (1) Color vibration warning: triggers an alarm when complementary colors are adjacent and the area ratio is greater than 1:3; (2) Layout density control: ensure that the negative space ratio is ≥25%; (3) Font level conflict detection: The title font size shall not exceed 300% of the main text size.

4. The method for quickly matching promotional images based on brand VI elements according to claim 1, characterized in that: The step 5 of real-time multimodal verification specifically includes: (1) Brand compliance verification: Real-time check of logo safety margins, primary color ratio, and font authorization status; (2) Media adaptation verification: Automatically adjust the resolution and color mode according to the output medium.

5. The method for quickly matching promotional images based on brand VI elements according to claim 1, characterized in that: The step 6 of incremental graph updating specifically updates the knowledge graph in the following way: (1) Record the element combination path of the user's final choice; (2) Strengthen the association weight of the selected path and weaken the unselected path; (3) When the weight change exceeds 30%, a version snapshot backup is triggered.

6. The method for quickly matching promotional images based on brand VI elements according to claim 1, characterized in that: The batch derivative output in step seven specifically includes automatically deriving size versions after the master draft is generated and applying style migration to maintain visual consistency among multiple versions. Among them, the following size versions are automatically derived after the master draft is generated: social media version (1080x1080 pixels), printed poster version (A3 / A4 resolution 300dpi) and mobile vertical version (9:16 ratio).

7. The method for quickly matching promotional images based on brand VI elements according to claim 1, characterized in that: The interactive correction implementation method of step eight is specifically as follows: S1. Mark the editable element hotspot on the preview interface; S2. Automatically lock the relative proportions of related elements when dragging and modifying; S3. Record the modification history and generate a traceable decision tree.

8. The method for quickly matching promotional images based on brand VI elements according to claim 1, characterized in that: The step nine of intelligent memory output specifically includes the following contents: (1) Establish personalized element preference profiles for users; (2) When similar scenarios are detected, the historical preferred combination is preferentially called; (3) Provide a comparison view of new and old solutions to assist decision-making.

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