METHOD, SYSTEM AND ELECTRONIC DEVICE FOR DIET MANAGEMENT

• US 20160350515A1
• Filed: 08/10/2016
• Published: 12/01/2016
• Est. Priority Date: 12/14/2012
• Status: Active Grant

• Current Assignee: Industrial Technology Research Institute
• Original Assignee: Industrial Technology Research Institute
• Inventors: Ting, Chuan-Wei, Wang, Ching-Yao, Chen, Ju-Chin
• Granted Patent: US 9,971,876 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/56 having vectorial format
• CPC Class Codes: G06F 16/5838 using colour
• CPC Class Codes: G06V 10/507 Summing image-intensity values; Histogram projection analysis
• CPC Class Codes: G06V 20/68 Food, e.g. fruit or vegetables
• CPC Class Codes: G09B 19/0092 Nutrition
• CPC Class Codes: G16H 20/60 relating to nutrition control, e.g. diets
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing

Abstract

An electronic device, a system and a method for diet management based on image analysis are provided. The system includes a computer and a database. The computer comprises a processor for performing the following operations: capturing at least one diet image via an image capture device; pre-processing the at least one diet image so as to obtain at least one diet region from the at least one diet image and obtain at least one detailed food segment from the diet region; extracting at least one diet image feature from the at least one detailed food segment; determining a diet type of the at least one detailed food segment based on the at least one diet image feature; and providing a personal diet characteristic analysis based on the diet type and an area of the at least one detailed food segment.

Claims

1. A computer-implemented method for diet management, adapted to a diet management system comprising a computer and a memory device used as a database, the computer comprises a processor and a plurality of program instructions, wherein the plurality of program instructions are loaded into the processor to perform the computer-implemented method, and the computer-implemented method comprising:

capturing at least one diet image via an image capture device;

pre-processing the at least one diet image so as to obtain at least one diet region from the at least one diet image and obtain at least one detailed food segment from the diet region;

extracting at least one diet image feature from the at least one detailed food segment;

determining a diet type of the at least one detailed food segment based on the at least one diet image feature; and

providing a personal diet characteristic analysis based on the diet type and an area of the at least one detailed food segment.

2. The method for diet management of claim 1, wherein the pre-processing the at least one diet image comprises:

transforming the at least one diet image to a normalized space.

3. The method for diet management of claim 1, wherein the pre-processing the at least one diet image comprises:

performing color correction, bright correction, or white balance correction on the at least one diet image;

performing background removal on the at least one diet image so as to obtain the at least one diet region; and

performing detailed food segment segmentation on the at least one diet region so as to segment out the at least one detailed food segment from the diet region.

4. The method for diet management of claim 1, wherein the at least one image feature comprises image capturing time, image capturing location, color, texture complexity, or reflectivity.

5. The method for diet management of claim 1, further comprises:

performing similarity comparison between the at least one diet image feature and at least one feature vectors in the database so as to determine the diet type of the at least one detailed food segment.

6. The method for diet management of claim 5, wherein the performing similarity comparison comprises:

calculating an Euclidean distance, an angle, a correlation coefficient, or mutual information between the at least one diet image feature and one of the feature vectors in the database.

7. The method for diet management of claim 1, wherein the determining the diet type of the at least one detailed food segment comprises:

performing similarity comparison in the database or via a diet type classifier.

8. A system for diet management comprising a computer and a memory device used as a database, the computer comprises a processor and a plurality of program instructions, wherein the plurality of program instructions are loaded into the processor to perform the following operations:

capturing at least one diet image via an image capture device;

pre-processing the at least one diet image so as to obtain at least one diet region from the at least one diet image and obtain at least one detailed food segment from the diet region;

extracting at least one diet image feature from the at least one detailed food segment;

determining a diet type of the at least one detailed food segment based on the at least one diet image feature; and

providing a personal diet characteristic analysis based on the diet type and an area of the at least one detailed food segment.

9. The system for diet management of claim 8, wherein the operation of pre-processing the at least one diet image comprises:

transforming the at least one diet image to a normalized space.

10. The system for diet management of claim 8, wherein the operation of pre-processing the at least one diet image comprises:

performing color correction, bright correction, or white balance correction on the at least one diet image;

performing background removal on the at least one diet image so as to obtain the at least one diet region; and

performing detailed food segment segmentation on the at least one diet region so as to segment out the at least one detailed food segment from the diet region.

11. The system for diet management of claim 8, wherein the at least one image feature comprises image capturing time, image capturing location, color, texture complexity, or reflectivity.

12. The system for diet management of claim 8, wherein the plurality of program instructions are loaded into the processor to further perform the following operations:

performing similarity comparison between the at least one diet image feature and at least one feature vectors in the database so as to determine the diet type of the at least one detailed food segment.

13. The system for diet management of claim 12, wherein the performing similarity comparison comprises:

calculating an Euclidean distance, an angle, a correlation coefficient, or mutual information between the at least one diet image feature and one of the feature vectors in the database.

14. The system for diet management of claim 8, wherein the operation of determining the diet type of the at least one detailed food segment comprises:

performing similarity comparison in the database or via a diet type classifier.

15. An electronic device comprising:

a database; and

a processing circuit, electrically coupled to the database, for capturing at least one diet image via an image capture device, pre-processing the at least one diet image so as to obtain at least one diet region from the at least one diet image and obtain at least one detailed food segment from the diet region, extracting at least one diet image feature from the at least one detailed food segment, determining a diet type of the at least one detailed food segment based on the at least one diet image feature, and providing a personal diet characteristic analysis based on the diet type and an area of the at least one detailed food segment.

16. The electronic device of claim 15, wherein the processing circuit transforms the at least one diet image to a normalized space.

17. The electronic device of claim 15, wherein the processing circuit performs color correction, bright correction, or white balance correction on the at least one diet image, the processing circuit performs background removal on the at least one diet image so as to obtain the at least one diet region, and the processing circuit performs detailed food segment segmentation on the at least one diet region so as to segment out the at least one detailed food segment from the diet region.

18. The electronic device of claim 15, wherein the at least one image feature comprises image capturing time, image capturing location, color, texture complexity, or reflectivity.

19. The electronic device of claim 15, wherein the processing circuit performs similarity comparison between the at least one diet image feature and at least one feature vectors in the database so as to determine the diet type of the at least one detailed food segment.

20. The electronic device of claim 19, wherein the processing circuit calculates an Euclidean distance, an angle, a correlation coefficient, or mutual information between the at least one diet image feature and one of the feature vectors in the database.

21. The electronic device of claim 15, wherein the processing circuit performs similarity comparison in the database or via a diet type classifier.