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Machine vision and edge AI notes — optics, lighting, algorithms, edge inference

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  • Edge AI (12)
  • Lighting Design (9)
  • Optics (22)
  • Vision Algorithm (23)

Recent posts

  • AOI Only Says “Defective” — How Vision Language Models Fill the Gap in Judgment Rationale 2026-09-17
  • There Are Defects That Vanish in Visible Light — Inspection Design Beyond the 1 μm Barrier in SWIR Imaging 2026-09-16
  • Catching 20 μm Sink Marks in High-Gloss Injection-Molded Parts with Phase Measuring Deflectometry (PMD) — The Last Gap Polarization Fusion Fills 2026-09-15
  • Where the μm Step Disappears: Measuring Both-Side Thickness Simultaneously with a Two-Channel Chromatic Confocal Controller 2026-09-10
  • Camera Interface Bandwidth Determines Resolution — From GigE Vision to CoaXPress 2.0 2026-09-09
Edge AI

Four Snags in Initial Jetson Orin Nano Setup

Four common snags in initial Jetson Orin Nano setup -- DisplayPort-only video output, QSPI firmware mismatch, SD/NVMe boot conflicts, and power-mode defaults.

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2026-08-05
Optics

The Defect Zone You Miss When You Switch to 3D Inspection

A 3D profiler's planar (xy) resolution is coarser than 2D line-scan. See how to route defects between 2D and 3D by measured contrast, not size, with WD and optical-setup specs.

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2026-08-19
Lighting Design, Optics

Keeping Frame Rate and Lighting from Colliding on a High-Speed Inspection Line

Push frame rate up and exposure time shrinks, taking light and contrast with it. How frame rate, illuminance, bandwidth, and strobe-trigger timing all have to be designed as one system…

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2026-08-27
  • Jetson Orin Nano 개발자 키트의 포트 배치와 부팅 매체 구성도
    Edge AI

    Four Snags in Initial Jetson Orin Nano Setup

    Noctvision / 2026-08-05 / 0 Comments

    Four common snags in initial Jetson Orin Nano setup -- DisplayPort-only video output, QSPI firmware mismatch, SD/NVMe boot conflicts, and power-mode defaults.

    read more
  • PCB 검사 화면 예시 — 좌측 룰베이스 고정 ROI, 우측 딥러닝 검출 박스
    Vision Algorithm

    Deep Learning vs. Rule-Based Algorithms: When to Use Which

    Noctvision / 2026-08-05 / 0 Comments

    A practical comparison of rule-based vision algorithms and deep learning, with clear criteria for which fits which inspection condition -- and why splitting roles beats picking one.

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  • 광학 분해능·노출 중 이동량·피사계심도 세 조건의 관계를 나타낸 도식
    Optics

    Machine-Vision Inspection: Physics Comes Before Software

    Noctvision / 2026-08-05 / 0 Comments

    Three physical quantities -- optical resolution, motion blur during exposure, and depth of field -- decide whether machine-vision inspection succeeds, before any algorithm work matters.

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  • 머신비전 조명 6가지 방식의 광원 배치와 빛의 경로 도식
    Lighting Design

    Six Machine-Vision Lighting Methods and How to Choose

    Noctvision / 2026-08-05 / 0 Comments

    Six industrial machine-vision lighting methods -- ring, bar, coaxial, back, dome, and low-angle -- with clear criteria for which fits which inspection target and surface.

    read more
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Categories

  • Edge AI (12)
  • Lighting Design (9)
  • Optics (22)
  • Vision Algorithm (23)

Recent posts

  • AOI Only Says “Defective” — How Vision Language Models Fill the Gap in Judgment Rationale 2026-09-17
  • There Are Defects That Vanish in Visible Light — Inspection Design Beyond the 1 μm Barrier in SWIR Imaging 2026-09-16
  • Catching 20 μm Sink Marks in High-Gloss Injection-Molded Parts with Phase Measuring Deflectometry (PMD) — The Last Gap Polarization Fusion Fills 2026-09-15
  • Where the μm Step Disappears: Measuring Both-Side Thickness Simultaneously with a Two-Channel Chromatic Confocal Controller 2026-09-10
  • Camera Interface Bandwidth Determines Resolution — From GigE Vision to CoaXPress 2.0 2026-09-09
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  • Optics
  • Lighting Design
  • Vision Algorithm
  • Edge AI
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