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Huawei H12-521_V1.0-ENU certification exam is intended for professionals who have a basic understanding of network and security technologies, as well as experience in the field of intelligent vision technology. Candidates who successfully pass H12-521_V1.0-ENU exam will be able to demonstrate their knowledge and skills in the field of intelligent vision technology, which can help them advance their careers and pursue new opportunities in the industry.
Huawei H12-521_V1.0-ENU Certification Exam is designed for professionals who are interested in obtaining the HCIP-Intelligent Vision V1.0 certification. HCIP-Intelligent Vision V1.0 certification focuses on the application and implementation of intelligent vision technologies in various industries. H12-521_V1.0-ENU Exam is a comprehensive test that covers a range of topics, including the fundamentals of intelligent vision, intelligent video surveillance, intelligent analysis and processing, and intelligent vision applications.
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Huawei H12-521_V1.0 (HCIP-Intelligent Vision V1.0) certification exam is designed for individuals who want to validate their knowledge and skills in the field of intelligent vision. HCIP-Intelligent Vision V1.0 certification exam is ideal for those who work with Huawei's intelligent vision solutions and want to enhance their expertise in this area. H12-521_V1.0-ENU Exam covers various topics related to intelligent vision, including the principles of intelligent vision, the development and deployment of intelligent vision solutions, and the use of artificial intelligence in intelligent vision.
Huawei HCIP-Intelligent Vision V1.0 Sample Questions (Q26-Q31):
NEW QUESTION # 26
In order to deal with different power supply scenarios, the power supply methods provided by the video site include () (Multiple choice)
- A. Electric hybrid solution
- B. Pure mains solution
- C. Optoelectronic solutions
- D. Pure light solution
Answer: A,B,C,D
NEW QUESTION # 27
The target recognition camera is usually set up at a height of 3.5-5 meters to achieve the maximum coverage.
Answer: A
NEW QUESTION # 28
The principle of license plate recognition technology includes character segmentation, license plate location, character recognition, image acquisition, etc.
Answer: A
NEW QUESTION # 29
The motorized zoom camera cannot adjust the focal length and focus on the camera web preview page.
Answer: A
NEW QUESTION # 30
During license plate recognition, the binary license plate image is horizontally projected along the Y axis to obtain the longest successive projection segment as the character area, and the successive horizontal black lines around the licence plate are filtered out. This method is called ( ).
- A. Horizontal projection
- B. Direction division
- C. Vertical projection
- D. Binary processing
Answer: A
Explanation:
The correct answer is C because the described method exactly matches the definition of horizontal projection used in license plate character area extraction. In license plate recognition, projection methods are commonly used to separate valid character regions from noise and borders. The material states that "Horizontal projection: The binary license plate image is horizontally projected along the Y axis to obtain the longest successive projection segment as the character area. Filter out horizontally successive black lines around the license plate." This wording is essentially identical to the question, so the method can be identified directly.
From an image-processing perspective, horizontal projection analyzes the pixel distribution across rows to locate the effective vertical range of the character band. This helps remove irrelevant black border lines above and below the plate characters. By contrast, vertical projection is mainly used later to segment individual characters because spaces naturally exist between them. Binary processing is a preprocessing step, not the named segmentation method here, and direction division is not the correct technical term in this context.
Therefore, the only correct choice is C. Horizontal projection .
NEW QUESTION # 31
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