text/microsoft-resx
2.0
System.Resources.ResXResourceReader, System.Windows.Forms, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089
System.Resources.ResXResourceWriter, System.Windows.Forms, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089
XplorePlane X-Ray Inspection System
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Scan Mode:
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Frame Merge:
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Acquisition Count:
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Real-Time Log Viewer
LogViewer - Window title
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Level Filter:
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Time
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Level
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Source
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Message
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Contrast Adjustment
Adjust image contrast and brightness
Contrast
Contrast gain, 1.0 for original contrast
Brightness
Brightness offset
Auto Contrast
Automatically stretch contrast to full range
Use CLAHE
Use Contrast Limited Adaptive Histogram Equalization
CLAHE Clip Limit
CLAHE contrast limit threshold
Band Pass Filter
Preserve image information within specified frequency range
Low Cutoff Radius
Components below this frequency will be removed
High Cutoff Radius
Components above this frequency will be removed
Filter Type
Transition characteristics of the filter
Butterworth Order
Order of Butterworth filter
Contour Detection
Detect contours in image and output contour information
Target Color
Select the color of regions to find (white or black)
Enable Threshold
Apply binary threshold before contour detection
Threshold Value
Threshold value for binarization (0-255)
Use Otsu Auto Threshold
Automatically calculate optimal threshold
Min Area
Filter contours smaller than this area
Max Area
Filter contours larger than this area
Line Thickness
Thickness of contour lines
Division Operation
Perform division operation on image for background correction and normalization
Divisor
Each pixel value will be divided by this number
Scale Factor
Division result multiplied by this scale factor
Normalize Output
Normalize result to 0-255 range
Gamma Correction
Adjust image brightness through Gamma value
Gamma Value
Gamma value, less than 1 darkens image, greater than 1 brightens image
Gain
Output gain coefficient
Gaussian Blur
Smooth image using Gaussian kernel
Kernel Size
Size of Gaussian kernel, must be odd
Standard Deviation
Standard deviation of Gaussian kernel, controls blur amount
Morphology Processing
Perform morphological operations (erosion, dilation, opening, closing)
Operation Type
Select morphological operation type
Kernel Size
Size of structuring element
Iterations
Number of times to repeat morphological operation
Shock Filter
Edge enhancement and denoising
Iterations
Number of filter iterations
Threshold
Edge detection threshold
Time Step
Evolution time step
Threshold Segmentation
Binarize image
Threshold
Binarization threshold, pixels above this value will be set to max value
Max Value
Pixels above threshold will be set to this value
Use Otsu Auto Threshold
When enabled, optimal threshold will be calculated automatically
Comprehensive Filter
Integrated multiple filtering methods
Filter Type
Select filtering method
Kernel Size
Size of the filter kernel (must be odd)
Sigma
Standard deviation for Gaussian/Bilateral filter
Cutoff Frequency
Cutoff frequency for frequency domain filtering
Low Cutoff Radius
Components below this frequency will be removed
High Cutoff Radius
Components above this frequency will be removed
Band Pass Filter Type
Transition characteristics of the band pass filter
Butterworth Order
Order of Butterworth filter
Gaussian Filter
Smooth image and reduce Gaussian noise while preserving edges
Median Filter
Remove salt-and-pepper noise effectively
Mean Filter
Simple averaging smoothing filter
Bilateral Filter
Edge-preserving smoothing filter
Low Pass Filter
Remove high frequency noise in frequency domain
High Pass Filter
Edge enhancement in frequency domain
Band Pass Filter
Preserve image information within specified frequency range
Median Filter
Remove salt-and-pepper noise effectively
Kernel Size
Size of the filter kernel (must be odd)
Mean Filter
Simple averaging smoothing filter
Kernel Size
Size of the filter kernel (must be odd)
Bilateral Filter
Edge-preserving smoothing filter
Diameter
Diameter of each pixel neighborhood
Sigma Color
Filter sigma in the color space
Sigma Space
Filter sigma in the coordinate space
Low Pass Filter
Remove high frequency noise in frequency domain
Cutoff Frequency
Cutoff frequency for low pass filter
High Pass Filter
Edge enhancement in frequency domain
Cutoff Frequency
Cutoff frequency for high pass filter
Grayscale Conversion
Convert image to grayscale
Conversion Method
Method for grayscale conversion
Sharpen
Enhance image edges and details
Sharpen Method
Select sharpening algorithm
Strength
Strength of sharpening effect
Kernel Size
Size of sharpening kernel (must be odd)
Histogram Equalization
Enhance image contrast
Equalization Method
Select histogram equalization algorithm
Clip Limit
Contrast limiting threshold for CLAHE
Tile Size
Tile size for CLAHE
Sobel Edge Detection
Detect image edges using Sobel operator
Detection Direction
Select edge detection direction
Kernel Size
Sobel operator kernel size (odd number)
Scale Factor
Scale factor for edge intensity
Kirsch Edge Detection
Detect image edges using Kirsch operator
Threshold
Edge detection threshold
Scale Factor
Scale factor for edge intensity
Horizontal Edge Detection
Detect horizontal edges specifically
Detection Method
Select horizontal edge detection algorithm
Sensitivity
Edge detection sensitivity
Threshold
Edge detection threshold
Retinex Shadow Correction
Multi-scale shadow correction and illumination equalization based on Retinex
Processing Method
Select Retinex algorithm type
Scale 1 (Small)
Small scale Gaussian kernel sigma for detail enhancement
Scale 2 (Medium)
Medium scale Gaussian kernel sigma for local illumination correction
Scale 3 (Large)
Large scale Gaussian kernel sigma for global illumination correction
Gain
Output gain factor
Offset
Output offset value
HDR Enhancement
High Dynamic Range image enhancement with tone mapping
Tone Mapping Method
Select HDR tone mapping algorithm: LocalToneMap, AdaptiveLog, Drago, BilateralToneMap
Gamma
Gamma correction value for output brightness adjustment
Saturation
Contrast saturation factor for LocalToneMap method
Detail Boost
Detail enhancement factor, higher values reveal more fine details
Sigma Space
Spatial sigma for base layer extraction, controls smoothing range
Sigma Color
Color sigma for bilateral tone mapping, controls edge preservation
Bias
Bias for adaptive logarithmic and Drago mapping, controls dark/bright balance
Mirror
Flip image horizontally, vertically, or both
Direction
Flip direction: Horizontal (left-right), Vertical (up-down), Both (180° rotation)
Rotate
Rotate image by arbitrary angle with optional canvas expansion
Angle
Rotation angle in degrees, positive is counter-clockwise
Expand Canvas
Expand canvas to fit the entire rotated image, otherwise crop to original size
Background
Background fill value (0-255) for areas outside the original image
Interpolation
Interpolation method: Nearest (fast), Bilinear (smooth), Bicubic (high quality)
Pseudo Color Rendering
Map grayscale image to color image using color maps
Color Map
Select color mapping table for rendering
Min Gray Value
Gray values below this will be clipped to minimum color
Max Gray Value
Gray values above this will be clipped to maximum color
Invert Color Map
Reverse the color mapping direction
Electronic Film Effect
Simulate traditional X-ray film display with window/level and characteristic curves
Window Center
Center gray value of the display window (Window Level)
Window Width
Width of the display window, controls visible gray range
Invert (Negative)
Invert image to negative film effect
Characteristic Curve
Film characteristic curve: Linear, Sigmoid (S-curve), Logarithmic, Exponential
Curve Strength
Strength of the characteristic curve effect
Edge Enhancement
Edge enhancement strength to simulate film sharpening, 0 to disable
Sub-Pixel Zoom
High-quality sub-pixel image magnification with multiple interpolation methods
Scale Factor
Magnification factor, supports fractional values (e.g. 1.5, 2.3)
Interpolation
Interpolation method: Nearest, Bilinear, Bicubic, Lanczos (highest quality)
Sharpen After Zoom
Apply sharpening after magnification to compensate interpolation blur
Sharpen Strength
Strength of post-zoom sharpening
Super Resolution (AI)
Deep learning based super resolution using EDSR/FSRCNN models
Model
Super resolution model: EDSR (high quality, slow) or FSRCNN (fast, lightweight)
Scale Factor
Upscaling factor: 2x, 3x, or 4x
Color Layer Separation
Separate grayscale image into distinct intensity layers
Layers
Number of intensity layers (2-16)
Method
Thresholding method: Uniform (equal intervals) or Otsu (adaptive)
Output Mode
Output mapping: EqualSpaced (evenly distributed) or MidValue (interval midpoint)
Target Layer
0 = show all layers, 1~N = show only the specified layer (white) with others black
Hierarchical Enhancement
Enhance image details at different scales using Laplacian pyramid decomposition
Pyramid Levels
Number of pyramid decomposition levels (2-8)
Fine Detail Gain
Gain for finest detail layer (edges, textures). 1.0 = original, >1 = enhance, <1 = suppress
Medium Detail Gain
Gain for medium-scale details. 1.0 = original, >1 = enhance, <1 = suppress
Coarse Detail Gain
Gain for coarse-scale details (large structures). 1.0 = original, >1 = enhance, <1 = suppress
Base Layer Gain
Gain for the base (lowest frequency) layer, controls overall brightness
Clip Limit
Limit detail amplitude to prevent over-enhancement artifacts. 0 = no limit
Histogram Overlay
Compute grayscale histogram and overlay it on the top-left corner of the image with statistics
Ellipse Detection
Detect ellipses in image using contour analysis and ellipse fitting
Min Threshold
Minimum threshold for dual-threshold segmentation (0-255)
Max Threshold
Maximum threshold for dual-threshold segmentation (0-255)
Use Otsu Auto Threshold
When enabled, optimal threshold will be calculated automatically
Min Contour Points
Minimum number of contour points for ellipse fitting
Min Area
Filter ellipses smaller than this area
Max Area
Filter ellipses larger than this area
Max Eccentricity
Maximum eccentricity (0=circle, close to 1=flat ellipse)
Max Fit Error
Maximum fitting error in pixels
Line Thickness
Thickness of ellipse drawing lines
Line Measurement
Measure distance between two points in the image
Point 1 X
X coordinate of the first point (pixels)
Point 1 Y
Y coordinate of the first point (pixels)
Point 2 X
X coordinate of the second point (pixels)
Point 2 Y
Y coordinate of the second point (pixels)
Pixel Size
Physical size per pixel for calibrated measurement
Unit
Measurement unit: px (pixels), mm, μm, cm
Line Thickness
Thickness of the measurement line
Show Label
Display distance label on the measurement line
Via Fill Rate (Tilted Geometric)
Measure via fill rate using 4-ellipse geometric projection on tilted X-Ray image
THT Limit (%)
Minimum fill rate to pass (default 75% per IPC-610)
Line Thickness
Thickness of ROI ellipse lines
BGA Void Rate (Auto)
Auto-detect BGA solder balls and measure void rate (two-step: locate BGA → detect voids)
BGA Min Area
Minimum pixel area to identify as a BGA solder ball
ROI Mode
None: full image; Polygon: polygon ROI (draw ROI first)
BGA Max Area
Maximum pixel area to identify as a BGA solder ball
Blur Kernel
Gaussian blur kernel size for BGA detection (odd number)
Min Circularity
Minimum circularity to filter non-circular contours (0~1, 1=perfect circle)
Void Limit (%)
Maximum allowed void rate (default 25% per IPC-7095)
Min Threshold
Minimum gray value for void detection (pixels in [Min,Max] = void)
Max Threshold
Maximum gray value for void detection
Min Void Area
Minimum pixel area to count as a void (filter noise)
Line Thickness
Thickness of contour lines
Point-to-Line Distance
Measure perpendicular distance from a point to a line
Pixel Size
Physical size per pixel for calibrated measurement
Unit
Measurement unit: px / mm / μm / cm
Line Thickness
Thickness of drawing lines
Rotated multi-target template matching
Rotation and multi-target matching via TemplateMatchLib, with pyramid levels and SIMD acceleration.
Template path
Path to the template image (grayscale or color; color is converted to grayscale).
Match threshold
Score threshold; typical range 0.7–0.95.
Max matches
Maximum number of targets to return.
Angle tolerance (°)
Angular search range in degrees; 0 disables rotation search.
Max overlap
Maximum allowed overlap ratio between multiple detections.
Min reduce area
Minimum pyramid level area (controls depth; smaller tends to be faster).
SIMD acceleration
Use SIMD (e.g. SSE) to accelerate matching.
Sub-pixel
Enable sub-pixel refinement (more accurate, slightly slower).
Draw results
Draw match rectangles and center marks on the output image.
Line thickness
Stroke width for rectangles and crosshairs (pixels).
Template file not found
Template learn failed
TemplateMatchLib.dll not found — build the C++ DLL project first.
Model path
Path to a pre-trained model file (.tmmodel). If it exists the model is loaded directly; otherwise the template is learned and the model is saved automatically.
ROI Alignment
Transform teach polygon ROI to the run image using reference and template-match poses (outputs Poly params for downstream inspectors).
Reference center X
Template/part center X on the teach image (pixels).
Reference center Y
Template/part center Y on the teach image (pixels).
Reference angle (°)
Reference angle on the teach image; usually 0.
Measured center X
Match center X on the current image; inject from previous step OutputData.
Measured center Y
Match center Y on the current image.
Measured angle (°)
Match angle on the current image.
Angle Measurement
Measure angle between two rays sharing a common vertex
Void Measurement
Detect voids in ROI and calculate void rate
Min Threshold
Lower grayscale bound for void detection
Max Threshold
Upper grayscale bound for void detection
Min Void Area
Voids smaller than this area are ignored (pixels)
Merge Radius
Dilation radius for merging adjacent voids (0=no merge)
Blur Size
Gaussian blur kernel size (odd number)
Void Limit (%)
Void rate above this limit is classified as FAIL
Emboss Pseudo-3D
Emboss effect simulating 3D relief for enhanced visualization of surface structures
Light Direction
Simulated light source direction for emboss effect
Emboss Depth
Depth of emboss effect (higher = stronger relief)
Original Blend
Blend ratio with original image (0=pure emboss, 1=original only)
Gray Offset
Gray level offset for flat areas (128=mid-gray base)
Bitwise OR Operation
Perform bitwise OR operation on images, supporting OR operation with fixed values, which can be used for image merging and mask operations.
Value
Value for bitwise OR operation with each pixel of the image (0–255)
Differential Operation
Perform differential operation on images, supporting horizontal, vertical and diagonal differentiation, which can be used for edge detection.
Direction
Differential Directions: Horizontal, Vertical, Both (Gradient Magnitude)
Normalized Output
Normalize the result to the range of 0-255.
Multiplication Operation
Perform multiplication operations on image pixel values, commonly used for image enhancement and contrast adjustment.
Multiplier
Pixel values are multiplied by this coefficient (0.1–10.0).
Normalized Output
Normalize the result to the range of 0–255
Integral Calculation
Compute the integral image (cumulative sum) for fast region summation.
Normalized Output
Normalize the result to the range of 0–255
Nine-Point Calibration Tool
Load Image
Load from CSV
Calibrate
Save Calibration
Load Calibration
Show World Coordinates
Calibration Points
Pixel X
Pixel Y
World X
World Y
Ready
Status: Image loaded
{0}
Right-click on image to view coordinate conversion
Status: Loaded {0} calibration points from CSV
{1}
Status: Calibration successful! Using {0} points
Status: Calibration failed
Status: Calibration saved to
{0}
Status: Calibration loaded from
{0}
Pixel coordinates: ({0:F2}, {1:F2})
World coordinates: ({2:F2}, {3:F2})
At least 4 calibration points required!
Success
Calibration completed!
Save successful!
Load successful!
Load failed!
Chessboard Calibration Tool
Add Images
Clear List
Calibrate
Save Calibration
Load Calibration
Undistort Image
Chessboard Parameters
Inner Corners Width:
Inner Corners Height:
Square Size (mm):
Calibration Images
Status Information
Ready
Added {0} images
Image list cleared
Calibrating, please wait...
Calibration successful!
Overall reprojection error: {0:F4} pixels
{1}
Calibration failed: {0}
Calibration saved:
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Calibration loaded:
{0}
Image undistorted:
{0}
Image {0}
Reprojection error: {1:F4} pixels
Preparing calibration...
Detecting corners ({0}/{1})
Performing camera calibration...
Calculating reprojection errors ({0}/{1})
Calibration complete
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At least 3 images required!
Insufficient valid images, need at least 3, current {0}
Save successful!
Load successful!
Calibration completed!
Image{0}: {1:F4} pixels
Edge Find Line Fit
Place calipers along a search line to detect edge points and fit a line (supports Least Squares and RANSAC)
Caliper Count
Number of calipers placed evenly along the search line
Caliper Width
Search length of each caliper (pixels), perpendicular to the search line
Edge Polarity
Edge direction: BrightToDark, DarkToBright, or Both
Edge Threshold
Gradient strength threshold; edges below this value are ignored
Smoothing Sigma
Gaussian smoothing standard deviation for noise suppression (larger = smoother)
Fit Method
Line fitting algorithm: LeastSquares or RANSAC (robust, rejects outliers)
RANSAC Threshold
RANSAC inlier distance threshold (pixels); points closer than this to the line are inliers
Line Thickness
Drawing thickness for result visualization
Edge Find Circle Fit
Place calipers along estimated circle to detect edge points and fit a circle (supports Least Squares and RANSAC)
Caliper Count
Number of calipers placed evenly around the circle
Caliper Width
Search length of each caliper along radial direction (pixels)
Edge Polarity
Edge direction: BrightToDark, DarkToBright, or Both
Edge Threshold
Gradient strength threshold; edges below this value are ignored
Smoothing Sigma
Gaussian smoothing standard deviation for noise suppression
Search Direction
Caliper search direction: Inward (toward center), Outward (away from center), Both
Fit Method
Circle fitting algorithm: LeastSquares or RANSAC (robust, rejects outliers)
RANSAC Threshold
RANSAC inlier distance threshold (pixels); points closer than this to the circle are inliers
Line Thickness
Drawing thickness for result visualization
Histogram — No data
ImageHistogramControl - Placeholder text when no image data
QFN Lead Pad Void Detection
Automatically detect QFN lead pads and measure void rate per pad (two-step: locate pads → detect voids)
ROI Mode
None: Full image; Polygon: Polygon ROI (select lead pad area)
Pad Blur Size
Gaussian blur kernel size for pad detection (odd number)
Pad Threshold Low
Lower gray threshold for pad segmentation (pads are dark regions)
Pad Threshold High
Upper gray threshold for pad segmentation
Morph Kernel Size
Closing kernel size to fill small holes inside pads
Min Pad Area
Minimum pixel area to be recognized as a lead pad (filter noise)
Max Pad Area
Maximum pixel area for a lead pad (exclude thermal pad)
Min Aspect Ratio
Minimum aspect ratio for lead pads (QFN pads are elongated, ratio > 1)
Void Threshold Low
Lower gray threshold for void detection (voids are bright regions)
Void Threshold High
Upper gray threshold for void detection
Min Void Area
Areas smaller than this are treated as noise (pixels)
Void Merge Radius
Dilation radius to merge adjacent voids (0 = no merge)
Void Rate Limit (%)
Max allowed void rate per lead pad (default 50%, ref IPC-7095)
Min Qualified Pad Area
Pads with area below this value are marked as FAIL (insufficient solder)
Thickness
Contour drawing line thickness
QFN Integrated Detection
After template-match alignment, automatically run center pad void and lead pad void inspections and aggregate the final classification.