🔖 v0.9.0

Author: Robdel12

CHANGELOG.md

@@ -5,37 +5,6 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
-## [0.10.0] - 2026-02-03
-
-## What's Changed
-
-### Added
-- **GMSD (Gradient Magnitude Similarity Deviation)** - New `includeGMSD` option for fast, edge-sensitive perceptual comparison
-  - Returns `gmsdScore` in results (0.0 = identical, higher = more different)
-  - Very fast compared to SSIM, ideal for detecting border/outline changes
-  - Based on Xue et al. 2014 research paper
-  - **Note:** GMSD requires images with identical dimensions. For variable-height comparisons, `gmsdScore` will be `null`
-- **Cluster Merging** - New `clusterMerge` option to consolidate fragmented text regions
-  - Simple API: `clusterMerge: true` enables with sensible defaults
-  - Advanced API: Pass an object with `horizontalDistance`, `yBandTolerance`, `maxHeightRatio`, `maxWidthRatio`
-  - Solves the "59 clusters for one date string" problem by intelligently merging nearby character-level changes into logical text regions
-  - Uses SWT-inspired heuristics (Epshtein et al. 2010) for horizontal-biased text detection
-
-**Full Changelog**: https://github.com/vizzly-testing/honeydiff/compare/v0.9.0...v0.10.0
-
-## [Unreleased]
-
-### Added
-- **GMSD (Gradient Magnitude Similarity Deviation)** - New `includeGMSD` option for fast, edge-sensitive perceptual comparison
-  - Returns `gmsdScore` in results (0.0 = identical, higher = more different)
-  - Very fast compared to SSIM, ideal for detecting border/outline changes
-  - Based on Xue et al. 2014 research paper
-- **Cluster Merging** - New `clusterMerge` option to consolidate fragmented text regions
-  - Simple API: `clusterMerge: true` enables with sensible defaults
-  - Advanced API: Pass an object with `horizontalDistance`, `yBandTolerance`, `maxHeightRatio`, `maxWidthRatio`
-  - Solves the "59 clusters for one date string" problem
-  - Uses SWT-inspired heuristics (Epshtein et al. 2010)
-
 ## [0.9.0] - 2026-01-26
 
 ## What's Changed

README.md

@@ -188,39 +188,10 @@ if (result.diffClusters) {
 | 2 | Default - filters single isolated pixels as rendering noise |
 | 3+ | More permissive - only larger clusters detected |
 
-**Cluster Merging for Text Regions:**
-
-Text changes often fragment into many small clusters (one per character). Enable cluster merging to consolidate them into logical regions:
-
-```javascript
-// Simple: enable with sensible defaults
-const result = await compare('img1.png', 'img2.png', {
-  includeClusters: true,
-  clusterMerge: true  // Merge nearby clusters (great for text)
-});
-
-// Advanced: tune the merging behavior
-const result = await compare('img1.png', 'img2.png', {
-  includeClusters: true,
-  clusterMerge: {
-    horizontalDistance: 15,  // Max gap between clusters to merge (pixels)
-    yBandTolerance: 5,       // Vertical tolerance for "same line"
-    maxHeightRatio: 2.0,     // Prevent merging very different sized clusters
-    maxWidthRatio: 3.0
-  }
-});
-
-// Before: "2024-01-01" detected as 59 clusters (one per character/gap)
-// After:  "2024-01-01" detected as 1-2 logical regions
-```
-
-Uses SWT-inspired heuristics from text detection research (Epshtein et al. 2010).
-
-### 6. Perceptual Similarity (SSIM & GMSD)
+### 6. Perceptual Similarity (SSIM)
 
 Beyond pixel counting - measure structural similarity from a human perception perspective.
 
-**SSIM (Structural Similarity Index)** - Overall perceptual similarity:
 ```javascript
 const result = await compare('img1.png', 'img2.png', {
   includeSSIM: true  // Note: Can be slow on large images
@@ -229,33 +200,13 @@ const result = await compare('img1.png', 'img2.png', {
 if (result.perceptualScore !== null) {
   console.log(`SSIM: ${result.perceptualScore.toFixed(3)}`);
   // Output: SSIM: 0.923 (0.0 = different, 1.0 = identical)
-}
-```
-
-**GMSD (Gradient Magnitude Similarity Deviation)** - Fast edge-sensitive metric:
-```javascript
-const result = await compare('img1.png', 'img2.png', {
-  includeGMSD: true  // Very fast, great for detecting structural changes
-});
-
-if (result.gmsdScore !== null) {
-  console.log(`GMSD: ${result.gmsdScore.toFixed(4)}`);
-  // Output: GMSD: 0.0234 (0.0 = identical, higher = more different)
 
-  if (result.gmsdScore < 0.05) {
-    console.log('Edges are very similar');
+  if (result.perceptualScore > 0.95) {
+    console.log('Images are perceptually very similar');
   }
 }
 ```
 
-GMSD is ideal for catching:
-- Border thickness changes
-- Font weight shifts
-- Icon updates
-- Any edge/outline regressions
-
-**Reference:** Xue et al. 2014 - "Gradient Magnitude Similarity Deviation: A Highly Efficient Perceptual Image Quality Index"
-
 ### 7. Tolerance & Color Spaces
 
 **RGB Mode (default)** - Exact matching with pixel tolerance:
@@ -607,22 +558,22 @@ All functions accept:
 ```typescript
 interface CompareOptions {
   // Basic options
-  threshold?: number;                   // CIEDE2000 Delta E threshold (default: 2.0)
+  pixelTolerance?: number;              // 0-255, ignore diffs below threshold (default: 0)
+  colorThreshold?: number;              // 0.0-1.0, YIQ mode threshold (default: 0.0 = RGB)
   antialiasing?: boolean;               // Ignore AA artifacts (default: true)
+  ignoreColors?: boolean;               // Brightness only (default: false)
   maxDiffs?: number;                    // Stop after N diffs (default: unlimited)
 
   // Analysis options
   includeDiffPixels?: boolean;          // List all diff pixels (memory intensive, default: false)
   includeClusters?: boolean;            // Spatial clustering (default: false)
   includeSSIM?: boolean;                // SSIM perceptual score (slow, default: false)
-  includeGMSD?: boolean;                // GMSD edge similarity (fast, default: false)
   minClusterSize?: number;              // Filter clusters smaller than this (default: 2)
-  clusterMerge?: boolean | {            // Merge nearby clusters (default: false)
-    horizontalDistance?: number;        // Max horizontal gap to merge (default: 15)
-    yBandTolerance?: number;            // Vertical "same line" tolerance (default: 5)
-    maxHeightRatio?: number;            // Max height ratio to merge (default: 2.0)
-    maxWidthRatio?: number;             // Max width ratio to merge (default: 3.0)
-  };
+
+  // Accessibility options
+  includeAccessibilityData?: boolean;   // RGB, luminance, WCAG (default: false)
+  checkColorBlindness?: boolean;        // Color blindness simulation (default: false)
+  colorBlindnessThreshold?: number;     // Visibility threshold 0-255 (default: 30.0)
 
   // Output options
   diffPath?: string;                    // Save diff image path
@@ -655,8 +606,7 @@ interface DiffResult {
   diffPixelsList: DiffPixel[] | null;   // Null unless includeDiffPixels enabled
   diffClusters: DiffCluster[] | null;   // Null unless includeClusters enabled
   intensityStats: IntensityStats | null; // Null unless includeDiffPixels enabled
-  perceptualScore: number | null;       // SSIM 0.0-1.0, null unless includeSSIM enabled
-  gmsdScore: number | null;             // GMSD 0.0+, null unless includeGMSD enabled
+  perceptualScore: number | null;       // 0.0-1.0, null unless includeSSIM enabled
 }
 ```
 

index.d.ts

@@ -91,67 +91,12 @@ export interface DiffResult {
   intensityStats: IntensityStats | null;
   /** SSIM (Structural Similarity Index) perceptual score 0.0-1.0 (null unless includeSSIM is enabled) */
   perceptualScore: number | null;
-  /**
-   * GMSD (Gradient Magnitude Similarity Deviation) score (null unless includeGMSD is enabled)
-   * Lower values (closer to 0.0) indicate more similar images
-   * Typical range: 0.0 to ~0.3 for natural images
-   */
-  gmsdScore: number | null;
 }
 
 // ============================================================================
 // Options
 // ============================================================================
 
-/**
- * Options for merging nearby clusters
- *
- * These heuristics are designed to merge fragmented text regions (like individual
- * characters in a date string) into logical regions while avoiding merging
- * unrelated visual changes.
- *
- * Inspired by the Stroke Width Transform (SWT) text detection algorithm:
- * Epshtein, B., Ofek, E., & Wexler, Y. (2010). "Detecting Text in Natural Scenes
- * with Stroke Width Transform." CVPR 2010.
- */
-export interface ClusterMergeOptions {
-  /**
-   * Maximum horizontal distance to merge clusters in same Y-band (pixels)
-   *
-   * Clusters within this horizontal distance and overlapping Y-ranges
-   * will be merged. Suitable for merging characters in text.
-   * @default 15
-   */
-  horizontalDistance?: number;
-
-  /**
-   * Maximum vertical tolerance for "same Y-band" (pixels)
-   *
-   * Clusters with Y-ranges within this tolerance of each other are
-   * considered to be on the same line.
-   * @default 5
-   */
-  yBandTolerance?: number;
-
-  /**
-   * Maximum height ratio between clusters to allow merging
-   *
-   * Prevents merging clusters of very different sizes (e.g., a word
-   * with a large image). Based on SWT heuristic.
-   * @default 2.0
-   */
-  maxHeightRatio?: number;
-
-  /**
-   * Maximum width ratio between clusters to allow merging
-   *
-   * Additional SWT-inspired heuristic to prevent merging dissimilar
-   * regions.
-   * @default 3.0
-   */
-  maxWidthRatio?: number;
-}
-
 export interface CompareOptions {
   /**
    * Perceptual color difference threshold using CIEDE2000 (Delta E units)
@@ -200,23 +145,6 @@ export interface CompareOptions {
    */
   includeSSIM?: boolean;
 
-  /**
-   * Calculate GMSD (Gradient Magnitude Similarity Deviation) score
-   *
-   * GMSD is very fast and highly sensitive to edge/structural changes.
-   * Useful for detecting border thickness changes, font weight shifts,
-   * and icon updates.
-   *
-   * **Note:** GMSD requires images with identical dimensions. For variable-height
-   * comparisons, `gmsdScore` will be `null`. Use SSIM for variable-height images.
-   *
-   * Reference: Xue et al. 2014 - "Gradient Magnitude Similarity Deviation:
-   * A Highly Efficient Perceptual Image Quality Index"
-   *
-   * @default false
-   */
-  includeGMSD?: boolean;
-
   /**
    * Minimum cluster size to count as a real difference
    *
@@ -233,28 +161,6 @@ export interface CompareOptions {
    */
   minClusterSize?: number;
 
-  /**
-   * Merge nearby clusters into logical regions
-   *
-   * When enabled, nearby clusters are merged using horizontal-biased heuristics
-   * that work well for text regions. This helps consolidate fragmented text
-   * changes (e.g., "2024-01-01" showing as 59 clusters) into logical regions.
-   *
-   * Automatically enables clustering when set.
-   *
-   * @default undefined (no merging)
-   *
-   * @example
-   * ```typescript
-   * // Simple: enable merging with sensible defaults
-   * { clusterMerge: true }
-   *
-   * // Advanced: tune the merging behavior
-   * { clusterMerge: { horizontalDistance: 20, yBandTolerance: 10 } }
-   * ```
-   */
-  clusterMerge?: boolean | ClusterMergeOptions;
-
   /**
    * Path to save the diff image (highlighted differences)
    * @default undefined

package.json

@@ -1,6 +1,6 @@
 {
   "name": "@vizzly-testing/honeydiff",
-  "version": "0.10.0",
+  "version": "0.9.0",
   "description": "High-performance image diffing for Node.js - Native bindings to Honeydiff Rust library",
   "type": "module",
   "main": "index.js",