House type image recognition method based on deep learning and image processing

A recognition method and image processing technology, which is applied in the field of artificial intelligence recognition, can solve the problems of no subdivision of house type map recognition types, low recognition accuracy rate, missed detection and false detection of recognition, etc.

Active Publication Date: 2020-10-23
上海品览数据科技有限公司
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AI Technical Summary

Problems solved by technology

[0003] There is no subdivision of the existing floor plan recognition types. A set of technologies is used for all floor plans, resulting in low recognition accuracy. Only through color, edge detection and line detection, without image pos...

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  • House type image recognition method based on deep learning and image processing
  • House type image recognition method based on deep learning and image processing
  • House type image recognition method based on deep learning and image processing

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Embodiment Construction

[0040] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0041] Such as Figure 1-5 As shown, the present invention is a method for identifying house type diagrams based on deep learning and image processing. The steps are as follows: the platform system identifies whether the house type diagram is a basic diagram category, a black and white diagram category, or a home decoration diagram category according to image recognition technology, and then respectively It should be handed over to the identification method of the ...

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Abstract

The invention discloses a house type image recognition method based on deep learning and image processing, and relates to the technical field of artificial intelligence recognition. The basic image type house type image recognition method is the same as a black and white image type house type image recognition method, and is carried out in two paths, and the method comprises the following steps: S1, obtaining a wall line segment set L1 through a first path; s2, obtaining a window line segment set L2 and a wall line segment set L3 of the outermost contour in a second path; s3, fusing results ofthe wall line segment set L1, the window line segment set L2 and the wall line segment set, and removing repeated line segments; s4, performing linear correction on the image according to the correction method; and S5, extracting a contour of the binary image, and outputting a json file. According to the method, the spatial positions of the house type images are identified for different categories, and the image processing and deep learning methods are combined, so that the house type image identification accuracy is high, the identification speed is high, manpower and material resources aregreatly liberated, and the efficiency is improved.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence recognition, and in particular relates to a house type map recognition method based on deep learning and image processing. Background technique [0002] With the rapid development of the economy and the real estate industry, people's demand for housing is increasing day by day, and there are many types of house plans in housing, and it is very time-consuming and labor-intensive to manually identify the styles of the house plans. With the improvement of computer vision and image processing technology, the use of computers to automatically identify floor plans and extract structures such as doors, windows, and walls in the floor plans can not only greatly liberate manpower, improve the efficiency of floor plan recognition, but also avoid Manual fatigue audits have the potential for misidentification. At present, the recognition of the house type map is based on the Huffman transform...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06K9/80
CPCG06V30/422G06V10/20G06F18/24
Inventor 魏勋
Owner 上海品览数据科技有限公司
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