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CCTV Video Analytics & Image Processing Flashcards

6 cards from real CCTV practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

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  1. What does Wide Dynamic Range (WDR) image processing improve in challenging lighting conditions?

    Answer: It balances bright and dark areas in the same frame so both are clearly visible

    WDR captures multiple exposures and combines them so details in both bright areas (like windows) and dark areas (like shadows) are rendered clearly in a single image.

  2. What is digital noise reduction (DNR) used for in CCTV camera image processing?

    Answer: To reduce the grainy visual artifacts that appear in low-light footage

    DNR algorithms analyze and smooth out the random pixel variations (grain/noise) caused by high ISO sensitivity in low-light conditions, producing cleaner images without reducing resolution.

  3. What does de-warping software do with video from a fisheye (360°) camera?

    Answer: Corrects the barrel distortion to produce flat, perspective-accurate views of specific zones

    De-warping applies mathematical transformations to the distorted circular image from a fisheye lens to produce multiple corrected views (pan-tilt-zoom virtual cameras) from a single physical camera.

  4. What is forensic video enhancement used for in a CCTV investigation?

    Answer: To improve the clarity, contrast, or detail of recorded footage to better identify persons or objects

    Forensic video enhancement uses noise reduction, deblurring, sharpening, and super-resolution tools to extract the maximum useful detail from low-quality recordings for use in investigations or legal proceedings.

  5. How does frame rate affect the effectiveness of video analytics?

    Answer: Higher frame rates improve detection accuracy for fast-moving objects and reduce missed events

    At low frame rates, fast-moving objects may skip through detection zones between frames, causing missed alerts; higher frame rates (15–30 fps) ensure analytics engines capture sufficient data points to track objects reliably.

  6. What is object classification in video analytics and why is it useful?

    Answer: Categorizing detected objects as person, vehicle, animal, etc., to reduce false alarms and focus alerts

    Object classification identifies the type of detected object so the system can, for example, alert on people crossing a boundary but ignore animals or blowing debris, significantly reducing false positive alarms.