diff --git a/packages/api/src/services/results/recognizeScore.ts b/packages/api/src/services/results/recognizeScore.ts
index 7b3124ee..2ef65528 100644
--- a/packages/api/src/services/results/recognizeScore.ts
+++ b/packages/api/src/services/results/recognizeScore.ts
@@ -73,8 +73,8 @@ export const recognizeScore = async (
             type: 'input_text',
             text:
               mix === 'Phoenix'
-                ? `Extract the vertically lined up white numbers from the photo according to the provided schema. One number per line, some numbers may have leading zeroes. All zeroes have a dot in the middle.`
-                : `Extract the vertically lined up white numbers from the photo according to the provided schema. One number per line, some numbers may have leading zeroes.`,
+                ? `Extract the vertically lined up numbers from the processed photo according to the provided schema. One number per line, some numbers may have leading zeroes. All zeroes have a dot in the middle.`
+                : `Extract the vertically lined up numbers from the processed photo according to the provided schema. One number per line, some numbers may have leading zeroes.`,
           },
           {
             type: 'input_image',
diff --git a/packages/web/src/features/leaderboards/AddResult.tsx b/packages/web/src/features/leaderboards/components/add-result/AddResult.tsx
similarity index 94%
rename from packages/web/src/features/leaderboards/AddResult.tsx
rename to packages/web/src/features/leaderboards/components/add-result/AddResult.tsx
index 381d56b3..b8697e88 100644
--- a/packages/web/src/features/leaderboards/AddResult.tsx
+++ b/packages/web/src/features/leaderboards/components/add-result/AddResult.tsx
@@ -17,7 +17,7 @@ import { FaExclamationCircle } from 'react-icons/fa';
 import { IoIosWarning } from 'react-icons/io';
 import { useNavigate, useParams } from 'react-router-dom';
 
-import css from './components/add-result/add-result.module.scss';
+import css from './add-result.module.scss';
 
 import { useConfirmationPopup } from 'components/ConfirmationPopup/useConfirmationPopup';
 import Loader from 'components/Loader/Loader';
@@ -29,10 +29,11 @@ import { useUser } from 'hooks/useUser';
 import { useLanguage } from 'utils/context/translation';
 import { api } from 'utils/trpc';
 
-import { ScreenshotRecognition } from './components/add-result/ScreenshotRecognition';
-import { compressDataUrl } from './components/add-result/compressFile';
-import { useProcessedImage } from './components/add-result/useProcessedImage';
-import { useSingleChartQuery } from './hooks/useSingleChartQuery';
+import { useSingleChartQuery } from '../../hooks/useSingleChartQuery';
+import { ImageDataPreview } from './ImageDataPreview';
+import { ScreenshotRecognition } from './ScreenshotRecognition';
+import { compressImageData } from './imageUtils';
+import { useProcessedImage } from './useProcessedImage';
 
 const GRADE_OPTIONS = [
   { value: 'SSS', label: 'SSS' },
@@ -196,7 +197,7 @@ const AddResult = () => {
     setError(null);
 
     try {
-      const compressedScreenshot = await compressDataUrl(processedImage.squareDataUrl);
+      const compressedScreenshot = await compressImageData(processedImage.imageData);
 
       const data = {
         pass: rawData.pass,
@@ -255,9 +256,8 @@ const AddResult = () => {
             <div className={css.splitPanels}>
               <div className={css.screenshotPanel}>
                 {processedImage && (
-                  <img
-                    src={processedImage.squareDataUrl}
-                    alt="Screenshot"
+                  <ImageDataPreview
+                    imageData={processedImage.imageData}
                     style={{ maxWidth: '100%', maxHeight: 270 }}
                   />
                 )}
@@ -329,7 +329,8 @@ const AddResult = () => {
             <>
               <ScreenshotRecognition
                 showDate
-                squareDataUrl={processedImage.squareDataUrl}
+                imageData={processedImage.imageData}
+                naturalSize={processedImage.naturalSize}
                 date={processedImage.date}
                 mix={form.values.mix}
                 onScoreRecognized={(score) => {
diff --git a/packages/web/src/features/leaderboards/components/add-result/ImageDataPreview.tsx b/packages/web/src/features/leaderboards/components/add-result/ImageDataPreview.tsx
new file mode 100644
index 00000000..8923ff89
--- /dev/null
+++ b/packages/web/src/features/leaderboards/components/add-result/ImageDataPreview.tsx
@@ -0,0 +1,23 @@
+import { useEffect, useRef } from 'react';
+
+interface ImageDataPreviewProps {
+  imageData: ImageData;
+  style?: React.CSSProperties;
+}
+
+export const ImageDataPreview = ({ imageData, style }: ImageDataPreviewProps) => {
+  const canvasRef = useRef<HTMLCanvasElement>(null);
+
+  useEffect(() => {
+    const canvas = canvasRef.current;
+    if (!canvas) return;
+    canvas.width = imageData.width;
+    canvas.height = imageData.height;
+    const ctx = canvas.getContext('2d');
+    if (ctx) {
+      ctx.putImageData(imageData, 0, 0);
+    }
+  }, [imageData]);
+
+  return <canvas ref={canvasRef} style={style} />;
+};
diff --git a/packages/web/src/features/leaderboards/components/add-result/ScreenshotRecognition.tsx b/packages/web/src/features/leaderboards/components/add-result/ScreenshotRecognition.tsx
index 2c11ece0..dc258e76 100644
--- a/packages/web/src/features/leaderboards/components/add-result/ScreenshotRecognition.tsx
+++ b/packages/web/src/features/leaderboards/components/add-result/ScreenshotRecognition.tsx
@@ -3,12 +3,17 @@ import { AreaSelector, type IArea } from '@bmunozg/react-image-area';
 import { Alert, Button, Group, Popover, Stack, Text } from '@mantine/core';
 import { useMutation } from '@tanstack/react-query';
 import imageCompression from 'browser-image-compression';
-import { useRef, useState } from 'react';
+import { useCallback, useEffect, useRef, useState } from 'react';
 
 import { useLanguage } from 'utils/context/translation';
 import { api } from 'utils/trpc';
 
-import { cropAreaToDataUrl } from './cropImage';
+import {
+  applyProcessing,
+  imageDataToCanvas,
+  prepareImageForRecognition,
+  shrinkAreaToBrightness,
+} from './imageUtils';
 
 export interface RecognizedScore {
   perfect: number;
@@ -21,7 +26,8 @@ export interface RecognizedScore {
 }
 
 interface ScreenshotRecognitionProps {
-  squareDataUrl: string;
+  imageData: ImageData;
+  naturalSize: number;
   date?: Date | null;
   showDate?: boolean;
   onScoreRecognized?: (score: RecognizedScore) => void;
@@ -29,19 +35,92 @@ interface ScreenshotRecognitionProps {
 }
 
 export const ScreenshotRecognition = ({
-  squareDataUrl,
+  imageData: originalImageData,
+  naturalSize,
   date,
   mix,
   showDate,
   onScoreRecognized,
 }: ScreenshotRecognitionProps) => {
+  const canvasRef = useRef<HTMLCanvasElement>(null);
+  const imageDataRef = useRef<ImageData | undefined>();
+
+  const drawToCanvas = (data: ImageData) => {
+    const canvas = canvasRef.current;
+    if (!canvas) return;
+    canvas.width = data.width;
+    canvas.height = data.height;
+    const ctx = canvas.getContext('2d');
+    if (ctx) {
+      ctx.putImageData(data, 0, 0);
+    }
+  };
+
+  useEffect(() => {
+    imageDataRef.current = structuredClone(originalImageData);
+    drawToCanvas(imageDataRef.current);
+    setAreas([]);
+  }, [originalImageData]);
+
   const lang = useLanguage();
   const [error, setError] = useState<string | null>(null);
   const [areas, setAreas] = useState<IArea[]>([]);
   const [recognizedNumbers, setRecognizedNumbers] = useState<number[] | null>(null);
-  // const [croppedPreview, setCroppedPreview] = useState<string | null>(null);
-  const imgRef = useRef<HTMLImageElement>(null);
+  const areaSelectorRef = useRef<HTMLDivElement>(null);
   const [isCropping, setIsCropping] = useState(false);
+  const [debugImage, setDebugImage] = useState<string>();
+  const isInteractingRef = useRef(false);
+  const areasRef = useRef(areas);
+  areasRef.current = areas;
+
+  const handleAreasChange = (newAreas: IArea[]) => {
+    isInteractingRef.current = true;
+    setAreas(newAreas);
+  };
+
+  const triggerShrink = useCallback(() => {
+    if (!isInteractingRef.current) return;
+    isInteractingRef.current = false;
+
+    const currentAreas = areasRef.current;
+
+    if (currentAreas.length === 0 || !canvasRef.current) return;
+
+    const area = currentAreas[0];
+    const displayedSize = canvasRef.current.clientWidth;
+
+    // crop to get a new area
+    const shrunkArea = shrinkAreaToBrightness(originalImageData, naturalSize, area, displayedSize);
+
+    if (imageDataRef.current) {
+      // apply processing filter to cropped area
+      const scale = naturalSize / displayedSize;
+      applyProcessing(
+        imageDataRef.current,
+        originalImageData,
+        Math.round(shrunkArea.x * scale),
+        Math.round(shrunkArea.y * scale),
+        Math.round(shrunkArea.width * scale),
+        Math.round(shrunkArea.height * scale)
+      );
+      drawToCanvas(imageDataRef.current);
+    }
+
+    setAreas([shrunkArea]);
+  }, [naturalSize, originalImageData]);
+
+  useEffect(() => {
+    const handlePointerUp = () => {
+      // trigger shrink after AreaSelector finishes event handling
+      setTimeout(triggerShrink, 0);
+    };
+
+    document.addEventListener('pointerup', handlePointerUp, { capture: true });
+
+    return () => {
+      document.removeEventListener('pointerup', handlePointerUp, { capture: true });
+    };
+  }, [triggerShrink]);
 
   const recognizeScoreMutation = useMutation(api.results.recognizeScoreMutation.mutationOptions());
 
@@ -49,20 +128,35 @@ export const ScreenshotRecognition = ({
   //   if (areas.length === 0 || !imgRef.current) return undefined;
   //   const area = areas[0];
   //   const displayedSize = imgRef.current.clientWidth;
-  //   cropAreaToDataUrl(squareDataUrl, area, displayedSize).then((t) => setCroppedPreview(t));
+  //   prepareImageForRecognition(squareDataUrl, area, displayedSize).then((t) =>
+  //     setCroppedPreview(t)
+  //   );
   // }, [squareDataUrl, areas]);
 
   const handleRecognizeScore = async () => {
-    if (areas.length === 0 || !imgRef.current) return;
+    if (areas.length === 0 || !canvasRef.current || !imageDataRef.current) return;
 
     try {
       setError(null);
       setIsCropping(true);
-      const displayedSize = imgRef.current.clientWidth;
-      const croppedImage = await cropAreaToDataUrl(squareDataUrl, areas[0], displayedSize);
+      const displayedSize = canvasRef.current.clientWidth;
+
+      // Get processed ImageData (synchronous)
+      const croppedImageData = prepareImageForRecognition(
+        originalImageData,
+        naturalSize,
+        areas[0],
+        displayedSize
+      );
 
-      // Compress the cropped image before sending for recognition
-      const croppedFile = await imageCompression.getFilefromDataUrl(croppedImage, 'cropped.png');
+      // Convert to canvas and compress for API
+      const croppedCanvas = imageDataToCanvas(croppedImageData);
+      const croppedFile = await imageCompression.canvasToFile(
+        croppedCanvas,
+        'image/png',
+        'cropped.png',
+        new Date().getTime()
+      );
       const compressedFile = await imageCompression(croppedFile, {
         maxWidthOrHeight: 360,
         maxSizeMB: 0.03,
@@ -70,6 +164,8 @@ export const ScreenshotRecognition = ({
       });
       const compressedImage = await imageCompression.getDataUrlFromFile(compressedFile);
 
+      setDebugImage(compressedImage);
+
       const numbers = await recognizeScoreMutation.mutateAsync({
         image: compressedImage,
         mix,
@@ -107,7 +203,7 @@ export const ScreenshotRecognition = ({
   };
 
   return (
-    <Stack gap="xs">
+    <Stack gap="xs" ref={areaSelectorRef}>
       {showDate && (
         <Text size="xs" c="dimmed">
           {lang.DATE_TAKEN}: {date ? date.toLocaleString() : lang.UNKNOWN}
@@ -116,19 +212,14 @@ export const ScreenshotRecognition = ({
 
       <AreaSelector
         areas={areas}
-        onChange={setAreas}
+        onChange={handleAreasChange}
         maxAreas={1}
         globalAreaStyle={{
           border: '1.5px solid rgba(0, 0, 0, 0.7)',
           outline: '1.5px solid rgba(255, 255, 128, 0.7)',
         }}
       >
-        <img
-          ref={imgRef}
-          style={{ maxWidth: '100%' }}
-          src={squareDataUrl}
-          alt="Screenshot preview"
-        />
+        <canvas ref={canvasRef} style={{ maxWidth: '100%', height: 'auto' }} />
       </AreaSelector>
 
       {/* {croppedPreview && <img src={croppedPreview} alt="Cropped preview" />} */}
@@ -173,46 +264,63 @@ export const ScreenshotRecognition = ({
       {recognizedNumbers && (
         <Alert color="blue" title={lang.RECOGNIZED_NUMBERS} radius="md">
           <Stack gap="xs">
-            <div style={{ display: 'grid', gridTemplateColumns: '1fr 1fr', gap: '0.2em' }}>
-              <Text size="sm" c="cyan">
-                Perfect:
-              </Text>
-              <Text size="sm" c="cyan">
-                {recognizedNumbers[0] >= 0 ? recognizedNumbers[0] : '?'}
-              </Text>
-              <Text size="sm" c="green">
-                Great:
-              </Text>
-              <Text size="sm" c="green">
-                {recognizedNumbers[1] >= 0 ? recognizedNumbers[1] : '?'}
-              </Text>
-              <Text size="sm" c="yellow">
-                Good:
-              </Text>
-              <Text size="sm" c="yellow">
-                {recognizedNumbers[2] >= 0 ? recognizedNumbers[2] : '?'}
-              </Text>
-              <Text size="sm" c="pink">
-                Bad:
-              </Text>
-              <Text size="sm" c="pink">
-                {recognizedNumbers[3] >= 0 ? recognizedNumbers[3] : '?'}
-              </Text>
-              <Text size="sm" c="red">
-                Miss:
-              </Text>
-              <Text size="sm" c="red">
-                {recognizedNumbers[4] >= 0 ? recognizedNumbers[4] : '?'}
-              </Text>
-              <Text size="sm">Combo:</Text>
-              <Text size="sm">{recognizedNumbers[5] >= 0 ? recognizedNumbers[5] : '?'}</Text>
-              <Text size="sm" fw="bold">
-                Score:
-              </Text>
-              <Text size="sm" fw="bold">
-                {recognizedNumbers[6] >= 0 ? recognizedNumbers[6] : '?'}
-              </Text>
-            </div>
+            <Group>
+              <div
+                style={{
+                  display: 'grid',
+                  gridTemplateColumns: '1fr min-content',
+                  gap: '0.2em',
+                  flex: '1 1 60%',
+                }}
+              >
+                <Text size="sm" c="cyan">
+                  Perfect:
+                </Text>
+                <Text size="sm" c="cyan" ta="right">
+                  {recognizedNumbers[0] >= 0 ? recognizedNumbers[0] : '?'}
+                </Text>
+                <Text size="sm" c="green">
+                  Great:
+                </Text>
+                <Text size="sm" c="green" ta="right">
+                  {recognizedNumbers[1] >= 0 ? recognizedNumbers[1] : '?'}
+                </Text>
+                <Text size="sm" c="yellow">
+                  Good:
+                </Text>
+                <Text size="sm" c="yellow" ta="right">
+                  {recognizedNumbers[2] >= 0 ? recognizedNumbers[2] : '?'}
+                </Text>
+                <Text size="sm" c="pink">
+                  Bad:
+                </Text>
+                <Text size="sm" c="pink" ta="right">
+                  {recognizedNumbers[3] >= 0 ? recognizedNumbers[3] : '?'}
+                </Text>
+                <Text size="sm" c="red">
+                  Miss:
+                </Text>
+                <Text size="sm" c="red" ta="right">
+                  {recognizedNumbers[4] >= 0 ? recognizedNumbers[4] : '?'}
+                </Text>
+                <Text size="sm">Combo:</Text>
+                <Text size="sm" ta="right">
+                  {recognizedNumbers[5] >= 0 ? recognizedNumbers[5] : '?'}
+                </Text>
+                <Text size="sm" fw="bold">
+                  Score:
+                </Text>
+                <Text size="sm" fw="bold" ta="right">
+                  {recognizedNumbers[6] >= 0 ? recognizedNumbers[6] : '?'}
+                </Text>
+              </div>
+              {debugImage && (
+                <img
+                  src={debugImage}
+                  style={{ maxHeight: '12em', objectFit: 'contain', flex: '1 1 30%' }}
+                />
+              )}
+            </Group>
             <Group gap="xs">
               <Button size="xs" color="blue" onClick={handleConfirmRecognition}>
                 {lang.FILL_FORM}
diff --git a/packages/web/src/features/leaderboards/components/add-result/compressFile.ts b/packages/web/src/features/leaderboards/components/add-result/compressFile.ts
deleted file mode 100644
index b46be177..00000000
--- a/packages/web/src/features/leaderboards/components/add-result/compressFile.ts
+++ /dev/null
@@ -1,15 +0,0 @@
-import imageCompression from 'browser-image-compression';
-
-export const compressFile = (file: File) => {
-  return imageCompression(file, { maxWidthOrHeight: 1400, maxSizeMB: 0.1, initialQuality: 0.7 });
-};
-
-export const compressDataUrl = async (dataUrl: string): Promise<string> => {
-  const file = await imageCompression.getFilefromDataUrl(dataUrl, 'image.jpg');
-  const compressed = await imageCompression(file, {
-    maxWidthOrHeight: 1200,
-    maxSizeMB: 0.1,
-    initialQuality: 0.8,
-  });
-  return imageCompression.getDataUrlFromFile(compressed);
-};
diff --git a/packages/web/src/features/leaderboards/components/add-result/cropImage.ts b/packages/web/src/features/leaderboards/components/add-result/cropImage.ts
deleted file mode 100644
index cde6eef0..00000000
--- a/packages/web/src/features/leaderboards/components/add-result/cropImage.ts
+++ /dev/null
@@ -1,52 +0,0 @@
-import type { IArea } from '@bmunozg/react-image-area';
-
-/**
- * Crops a selected area from a square image and returns a base64 data URL.
- * @param displayedSize - The size of the square image as displayed on screen
- */
-export const cropAreaToDataUrl = (
-  imageSrc: string,
-  area: IArea,
-  displayedSize: number
-): Promise<string> => {
-  return new Promise((resolve, reject) => {
-    const img = new Image();
-    img.onload = () => {
-      const canvas = document.createElement('canvas');
-      const ctx = canvas.getContext('2d');
-
-      if (!ctx) {
-        reject(new Error('Could not get canvas context'));
-        return;
-      }
-
-      // Scale coordinates from displayed size to natural size
-      const scale = img.naturalWidth / displayedSize;
-
-      const scaledX = area.x * scale;
-      const scaledY = area.y * scale;
-      const scaledWidth = area.width * scale;
-      const scaledHeight = area.height * scale;
-
-      canvas.width = scaledWidth;
-      canvas.height = scaledHeight;
-
-      ctx.drawImage(
-        img,
-        scaledX,
-        scaledY,
-        scaledWidth,
-        scaledHeight,
-        0,
-        0,
-        scaledWidth,
-        scaledHeight
-      );
-
-      resolve(canvas.toDataURL('image/jpeg', 0.95));
-    };
-
-    img.onerror = () => reject(new Error('Failed to load image'));
-    img.src = imageSrc;
-  });
-};
diff --git a/packages/web/src/features/leaderboards/components/add-result/getDate.ts b/packages/web/src/features/leaderboards/components/add-result/getDate.ts
deleted file mode 100644
index 5c22f473..00000000
--- a/packages/web/src/features/leaderboards/components/add-result/getDate.ts
+++ /dev/null
@@ -1,14 +0,0 @@
-import { parse } from 'exif-date';
-import * as ExifReader from 'exifreader';
-
-export const getDateFromFile = async (file: string | File) => {
-  const data = await ExifReader.load(file);
-  const dateString =
-    data.DateTimeOriginal?.description ||
-    data.DateTimeDigitized?.description ||
-    data.DateTime?.description;
-
-  if (typeof dateString !== 'string') return null;
-
-  return parse(dateString);
-};
diff --git a/packages/web/src/features/leaderboards/components/add-result/imageUtils.ts b/packages/web/src/features/leaderboards/components/add-result/imageUtils.ts
new file mode 100644
index 00000000..a9b8cf6b
--- /dev/null
+++ b/packages/web/src/features/leaderboards/components/add-result/imageUtils.ts
@@ -0,0 +1,223 @@
+import type { IArea } from '@bmunozg/react-image-area';
+import imageCompression from 'browser-image-compression';
+import { parse } from 'exif-date';
+import * as ExifReader from 'exifreader';
+
+/**
+ * Creates a canvas element from ImageData (cheap pixel copy, no decoding)
+ */
+export const imageDataToCanvas = (imageData: ImageData): HTMLCanvasElement => {
+  const canvas = document.createElement('canvas');
+  canvas.width = imageData.width;
+  canvas.height = imageData.height;
+  const ctx = canvas.getContext('2d');
+  if (ctx) {
+    ctx.putImageData(imageData, 0, 0);
+  }
+  return canvas;
+};
+
+export const getDateFromFile = async (file: string | File) => {
+  const data = await ExifReader.load(file);
+  const dateString =
+    data.DateTimeOriginal?.description ||
+    data.DateTimeDigitized?.description ||
+    data.DateTime?.description;
+
+  if (typeof dateString !== 'string') return null;
+
+  return parse(dateString);
+};
+
+export const compressImageData = async (imageData: ImageData): Promise<string> => {
+  const canvas = imageDataToCanvas(imageData);
+  const file = await imageCompression.canvasToFile(canvas, 'image/jpeg', 'image.jpg', 0.95);
+  const compressed = await imageCompression(file, {
+    maxWidthOrHeight: 1200,
+    maxSizeMB: 0.1,
+    initialQuality: 0.8,
+  });
+  return imageCompression.getDataUrlFromFile(compressed);
+};
+
+/**
+ * Calculates how "white" a pixel is (0-255).
+ * White pixels have high values in all channels and similar R, G, B values.
+ * This prioritizes white text over bright colorful backgrounds.
+ */
+const getWhiteness = (r: number, g: number, b: number): number => {
+  // Minimum channel value (a white pixel has all channels high)
+  const minChannel = Math.min(r, g, b);
+
+  // Color spread (white has low spread, colorful has high spread)
+  const maxChannel = Math.max(r, g, b);
+  const spread = maxChannel - minChannel;
+
+  return Math.min(255, Math.max(0, Math.round(minChannel ** 3 / 240 ** 2) - spread * 1));
+};
+
+/**
+ * Shrinks a selection area to fit the white text content within it.
+ * Finds the bounding box of the top X% whitest pixels (prioritizes pixels
+ * that are bright AND have low color saturation, i.e., close to white).
+ * Synchronous - works directly with ImageData.
+ * @param imageData - The source image pixel data
+ * @param naturalSize - The natural size of the square image
+ * @param area - The selected area in display coordinates
+ * @param displayedSize - The size of the image as displayed on screen
+ * @param brightnessPercentile - What percentile of whiteness to consider as "white" (0-100, default 95)
+ */
+export const shrinkAreaToBrightness = (
+  imageData: ImageData,
+  naturalSize: number,
+  area: IArea,
+  displayedSize: number,
+  brightnessPercentile = 95
+): IArea => {
+  const sourcePixels = imageData.data;
+  const sourceWidth = imageData.width;
+
+  // Scale coordinates from displayed size to natural size
+  const scale = naturalSize / displayedSize;
+
+  const scaledX = Math.round(area.x * scale);
+  const scaledY = Math.round(area.y * scale);
+  const scaledWidth = Math.round(area.width * scale);
+  const scaledHeight = Math.round(area.height * scale);
+
+  // Calculate whiteness for pixels in the selected area
+  const whitenessMap: number[] = [];
+  for (let y = 0; y < scaledHeight; y++) {
+    for (let x = 0; x < scaledWidth; x++) {
+      const sourceX = scaledX + x;
+      const sourceY = scaledY + y;
+      const i = (sourceY * sourceWidth + sourceX) * 4;
+      const whiteness = getWhiteness(sourcePixels[i], sourcePixels[i + 1], sourcePixels[i + 2]);
+      whitenessMap.push(whiteness);
+    }
+  }
+
+  // Find the whiteness threshold (top X percentile)
+  const sortedWhiteness = [...whitenessMap].sort((a, b) => b - a);
+  const thresholdIndex = Math.floor((sortedWhiteness.length * (100 - brightnessPercentile)) / 100);
+  const whitenessThreshold = sortedWhiteness[thresholdIndex] || 200;
+
+  // Find bounding box of white pixels
+  let minX = scaledWidth;
+  let maxX = 0;
+  let minY = scaledHeight;
+  let maxY = 0;
+
+  for (let y = 0; y < scaledHeight; y++) {
+    for (let x = 0; x < scaledWidth; x++) {
+      const idx = y * scaledWidth + x;
+      if (whitenessMap[idx] >= whitenessThreshold) {
+        minX = Math.min(minX, x);
+        maxX = Math.max(maxX, x);
+        minY = Math.min(minY, y);
+        maxY = Math.max(maxY, y);
+      }
+    }
+  }
+
+  // If no white pixels found, return original area
+  if (minX >= maxX || minY >= maxY) {
+    return area;
+  }
+
+  // Add small padding
+  const paddingX = Math.max(4, (maxX - minX) * 0.025);
+  const paddingY = Math.max(3, (maxY - minY) * 0.02);
+
+  minX = Math.max(0, minX - paddingX);
+  maxX = Math.min(scaledWidth, maxX + paddingX);
+  minY = Math.max(0, minY - paddingY);
+  maxY = Math.min(scaledHeight, maxY + paddingY);
+
+  // Convert back to display coordinates
+  const newArea: IArea = {
+    ...area,
+    x: area.x + minX / scale,
+    y: area.y + minY / scale,
+    width: (maxX - minX) / scale,
+    height: (maxY - minY) / scale,
+  };
+
+  return newArea;
+};
+
+export const applyProcessing = (
+  imageData: ImageData,
+  originalImageData: ImageData,
+  left: number,
+  top: number,
+  width: number,
+  height: number
+) => {
+  const sourcePixels = originalImageData.data;
+
+  for (let i = 0; i < sourcePixels.length; i++) {
+    imageData.data[i] = sourcePixels[i];
+  }
+
+  for (let y = 0; y < height; y++) {
+    for (let x = 0; x < width; x++) {
+      const sourceX = left + x;
+      const sourceY = top + y;
+      const i = (sourceY * imageData.width + sourceX) * 4;
+      const whiteness = getWhiteness(sourcePixels[i], sourcePixels[i + 1], sourcePixels[i + 2]);
+      imageData.data[i] = 255 - whiteness;
+      imageData.data[i + 1] = 255 - whiteness;
+      imageData.data[i + 2] = 255 - whiteness;
+      imageData.data[i + 3] = 255;
+    }
+  }
+};
+
+/**
+ * Crops a selected area from ImageData and applies whiteness processing.
+ * Returns processed ImageData ready for OCR.
+ * @param imageData - The source image pixel data
+ * @param naturalSize - The natural size of the square image
+ * @param area - The selected area in display coordinates
+ * @param displayedSize - The size of the square image as displayed on screen
+ */
+export const prepareImageForRecognition = (
+  imageData: ImageData,
+  naturalSize: number,
+  area: IArea,
+  displayedSize: number
+): ImageData => {
+  const sourcePixels = imageData.data;
+  const sourceWidth = imageData.width;
+
+  // Scale coordinates from displayed size to natural size
+  const scale = naturalSize / displayedSize;
+
+  const scaledX = Math.round(area.x * scale);
+  const scaledY = Math.round(area.y * scale);
+  const scaledWidth = Math.round(area.width * scale);
+  const scaledHeight = Math.round(area.height * scale);
+
+  // Create new ImageData for the cropped region
+  const croppedImageData = new ImageData(scaledWidth, scaledHeight);
+  const destPixels = croppedImageData.data;
+
+  // Copy pixels from source to destination with whiteness processing
+  for (let y = 0; y < scaledHeight; y++) {
+    for (let x = 0; x < scaledWidth; x++) {
+      const sourceX = scaledX + x;
+      const sourceY = scaledY + y;
+      const srcIdx = (sourceY * sourceWidth + sourceX) * 4;
+      const destIdx = (y * scaledWidth + x) * 4;
+      destPixels[destIdx] = sourcePixels[srcIdx];
+      destPixels[destIdx + 1] = sourcePixels[srcIdx + 1];
+      destPixels[destIdx + 2] = sourcePixels[srcIdx + 2];
+      destPixels[destIdx + 3] = sourcePixels[srcIdx + 3];
+    }
+  }
+
+  applyProcessing(croppedImageData, croppedImageData, 0, 0, scaledWidth, scaledHeight);
+
+  return croppedImageData;
+};
diff --git a/packages/web/src/features/leaderboards/components/add-result/useProcessedImage.ts b/packages/web/src/features/leaderboards/components/add-result/useProcessedImage.ts
index 46e9a9aa..7d67913c 100644
--- a/packages/web/src/features/leaderboards/components/add-result/useProcessedImage.ts
+++ b/packages/web/src/features/leaderboards/components/add-result/useProcessedImage.ts
@@ -1,53 +1,43 @@
 import { useEffect, useState } from 'react';
 
-import { getDateFromFile } from './getDate';
+import { getDateFromFile } from './imageUtils';
 
 export interface ProcessedImage {
-  squareDataUrl: string;
+  imageData: ImageData;
+  naturalSize: number;
   date: Date | null;
 }
 
+interface CropResult {
+  imageData: ImageData;
+  naturalSize: number;
+}
+
 /**
- * Crops an image to a centered square and returns as dataUrl
+ * Crops an image to a centered square and returns ImageData
+ * Uses createImageBitmap for efficient off-main-thread decoding
  */
-const cropToSquare = (imageSrc: string): Promise<string> => {
-  return new Promise((resolve, reject) => {
-    const img = new Image();
-    img.onload = () => {
-      const size = Math.min(img.naturalWidth, img.naturalHeight);
-      const x = (img.naturalWidth - size) / 2;
-      const y = (img.naturalHeight - size) / 2;
-
-      const canvas = document.createElement('canvas');
-      canvas.width = size;
-      canvas.height = size;
-      const ctx = canvas.getContext('2d');
-      if (!ctx) {
-        reject(new Error('Could not get canvas context'));
-        return;
-      }
+const cropToSquare = async (file: File): Promise<CropResult> => {
+  const bitmap = await createImageBitmap(file);
 
-      ctx.drawImage(img, x, y, size, size, 0, 0, size, size);
-      resolve(canvas.toDataURL('image/jpeg', 0.95));
-    };
-    img.onerror = () => reject(new Error('Failed to load image'));
-    img.src = imageSrc;
-  });
-};
+  const size = Math.min(bitmap.width, bitmap.height);
+  const x = (bitmap.width - size) / 2;
+  const y = (bitmap.height - size) / 2;
 
-const fileToDataUrl = (file: File): Promise<string> => {
-  return new Promise((resolve, reject) => {
-    const fr = new FileReader();
-    fr.onload = () => {
-      if (typeof fr.result === 'string') {
-        resolve(fr.result);
-      } else {
-        reject(new Error('Invalid file'));
-      }
-    };
-    fr.onerror = () => reject(new Error('Failed to read file'));
-    fr.readAsDataURL(file);
-  });
+  const canvas = document.createElement('canvas');
+  canvas.width = size;
+  canvas.height = size;
+  const ctx = canvas.getContext('2d');
+  if (!ctx) {
+    bitmap.close();
+    throw new Error('Could not get canvas context');
+  }
+
+  ctx.drawImage(bitmap, x, y, size, size, 0, 0, size, size);
+  bitmap.close();
+
+  const imageData = ctx.getImageData(0, 0, size, size);
+  return { imageData, naturalSize: size };
 };
 
 interface UseProcessedImageResult {
@@ -73,13 +63,13 @@ export const useProcessedImage = (file: File | null): UseProcessedImageResult =>
       setError(null);
 
       try {
-        const originalDataUrl = await fileToDataUrl(file);
-        const [squareDataUrl, date] = await Promise.all([
-          cropToSquare(originalDataUrl),
-          getDateFromFile(originalDataUrl),
-        ]);
+        const [cropResult, date] = await Promise.all([cropToSquare(file), getDateFromFile(file)]);
 
-        setProcessedImage({ squareDataUrl, date });
+        setProcessedImage({
+          imageData: cropResult.imageData,
+          naturalSize: cropResult.naturalSize,
+          date,
+        });
       } catch (e) {
         setError(e instanceof Error ? e.message : 'Failed to process image');
         setProcessedImage(null);
diff --git a/packages/web/src/features/root/Root.tsx b/packages/web/src/features/root/Root.tsx
index 2538c22d..342edec7 100644
--- a/packages/web/src/features/root/Root.tsx
+++ b/packages/web/src/features/root/Root.tsx
@@ -15,7 +15,7 @@ import { RegistrationPage } from 'features/login/Registration';
 
 import { useUser } from 'hooks/useUser';
 
-const LazyAddResult = React.lazy(() => import('../leaderboards/AddResult'));
+const LazyAddResult = React.lazy(() => import('../leaderboards/components/add-result/AddResult'));
 const LazySingleChartLeaderboard = React.lazy(
   () => import('../leaderboards/LeaderboardsSingleChart')
 );
diff --git a/packages/web/src/utils/base64.ts b/packages/web/src/utils/base64.ts
deleted file mode 100644
index 01e2a03c..00000000
--- a/packages/web/src/utils/base64.ts
+++ /dev/null
@@ -1,7 +0,0 @@
-export const toBase64 = (file: File) =>
-  new Promise<string>((resolve, reject) => {
-    const reader = new FileReader();
-    reader.readAsDataURL(file);
-    reader.onload = () => resolve(reader.result?.toString() ?? '');
-    reader.onerror = reject;
-  });