20240020843. METHOD FOR DETECTING AND SEGMENTING THE LIP REGION simplified abstract (BOTICA COMERCIAL FARMACÊUTICA LTDA.)

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METHOD FOR DETECTING AND SEGMENTING THE LIP REGION

Organization Name

BOTICA COMERCIAL FARMACÊUTICA LTDA.

Inventor(s)

Milene Haraguchi Padilha of Curitiba - PR (BR)

Camila Andréia Bernardon Urio of São José dos Pinhais - PR (BR)

Clarice Scliar Sasson of Curitiba - PR (BR)

Gustavo De Campos Dieamant of Curitiba - PR (BR)

METHOD FOR DETECTING AND SEGMENTING THE LIP REGION - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240020843 titled 'METHOD FOR DETECTING AND SEGMENTING THE LIP REGION

Simplified Explanation

The present patent relates to a method for reading and identifying patterns, specifically in the context of lip images. The technology utilizes algorithms of deep learning, machine learning, and artificial intelligence to detect and segment the lip region.

  • The method involves extracting input features from lip images and labeling them for training.
  • A processing module in a lip product application system is used to define and indicate the labeled lip images with pattern recognition algorithms.
  • A machine learning model is trained in the processing module using exemplified data and respective answers defining labels.
  • The trained model can then identify and generate a mathematical pattern for a lip product application system.

Potential applications of this technology:

  • Lip product development: The technology can be used to analyze lip images and generate mathematical patterns that aid in the development of lip products such as lipsticks, lip glosses, and lip balms.
  • Virtual try-on: By accurately identifying and segmenting the lip region, the technology can enable virtual try-on applications where users can see how different lip products would look on their own lips.
  • Beauty industry: The technology can be utilized in various beauty-related applications, including personalized makeup recommendations, virtual makeup tutorials, and beauty trend analysis.

Problems solved by this technology:

  • Accurate lip region detection: The technology addresses the challenge of accurately detecting and segmenting the lip region in images, which is crucial for various lip-related applications.
  • Pattern recognition: By utilizing deep learning, machine learning, and artificial intelligence algorithms, the technology improves the accuracy and efficiency of pattern recognition in lip images.
  • Training data generation: The technology provides a method for generating labeled training data, which is essential for training machine learning models.

Benefits of this technology:

  • Enhanced lip product development: The technology enables the creation of lip products that are tailored to individual lip shapes and contours, resulting in improved customer satisfaction.
  • Time and cost savings: By automating the lip region detection and pattern recognition process, the technology reduces the time and cost required for manual analysis and labeling of lip images.
  • Personalized beauty experiences: The technology allows for personalized recommendations and virtual try-on experiences, enhancing customer engagement and satisfaction in the beauty industry.


Original Abstract Submitted

the present patent of invention pertains to the technical field of methods or arrangements for reading and identifying patterns. more specifically, it refers to the technology for using alogrithms of deep learning, machine learning and artificial intelligence to identify the outline of lips and to methods enabling the detection and segmentation of the lip region. the method for detecting and segmenting the lip region of the present invention comprises recognizing patterns by extracting input features from lip images, labelling them for a training base by means of a processing module in a lip product application system; defining and indicating the labelled lip images with algorithms for recognizing patterns for said lip images to be learnt and segmented by said processing module; and training a machine learning model in said processing module with a plurality of exemplified data and respective answers defining labels that the model should learn and predict to identify and generate a mathematical pattern for a lip product application system.