diff --git a/.vscode/c_cpp_properties.json b/.vscode/c_cpp_properties.json
new file mode 100644
index 00000000..862aed87
--- /dev/null
+++ b/.vscode/c_cpp_properties.json
@@ -0,0 +1,16 @@
+{
+    "configurations": [
+        {
+            "name": "Linux",
+            "includePath": [
+                "${workspaceFolder}/**"
+            ],
+            "defines": [],
+            "compilerPath": "/usr/bin/gcc",
+            "cStandard": "gnu17",
+            "cppStandard": "gnu++14",
+            "intelliSenseMode": "linux-gcc-x64"
+        }
+    ],
+    "version": 4
+}
\ No newline at end of file
diff --git a/.vscode/settings.json b/.vscode/settings.json
index 9b5fdd53..20f06d5a 100644
--- a/.vscode/settings.json
+++ b/.vscode/settings.json
@@ -47,6 +47,22 @@
         "streambuf": "cpp",
         "cinttypes": "cpp",
         "typeinfo": "cpp",
-        "files.eol": "\n"
+        "files.eol": "\n",
+        "bitset": "cpp",
+        "chrono": "cpp",
+        "complex": "cpp",
+        "condition_variable": "cpp",
+        "cstring": "cpp",
+        "ctime": "cpp",
+        "set": "cpp",
+        "ratio": "cpp",
+        "regex": "cpp",
+        "future": "cpp",
+        "iomanip": "cpp",
+        "mutex": "cpp",
+        "shared_mutex": "cpp",
+        "thread": "cpp",
+        "variant": "cpp",
+        "list": "cpp"
     }
 }
\ No newline at end of file
diff --git a/documentation/man-database.h b/documentation/man-database.h
new file mode 100644
index 00000000..684260d5
--- /dev/null
+++ b/documentation/man-database.h
@@ -0,0 +1,237 @@
+unsigned char documentation_database_txt[] = {
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+};
+unsigned int documentation_database_txt_len = 2803;
diff --git a/documentation/man-pipeline.h b/documentation/man-pipeline.h
new file mode 100644
index 00000000..98331db9
--- /dev/null
+++ b/documentation/man-pipeline.h
@@ -0,0 +1,1313 @@
+unsigned char documentation_pipeline_txt[] = {
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+  0x5f, 0x08, 0x68, 0x5f, 0x08, 0x6f, 0x5f, 0x08, 0x6c, 0x5f, 0x08, 0x64,
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+  0x67, 0x20, 0x61, 0x6c, 0x67, 0x6f, 0x72, 0x69, 0x74, 0x68, 0x6d, 0x73,
+  0x0a, 0x0a, 0x0a, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x2d, 0x08,
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+  0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x43, 0x68, 0x6f, 0x6f,
+  0x73, 0x65, 0x73, 0x20, 0x5f, 0x08, 0x66, 0x5f, 0x08, 0x69, 0x5f, 0x08,
+  0x6c, 0x5f, 0x08, 0x65, 0x5f, 0x08, 0x6e, 0x5f, 0x08, 0x61, 0x5f, 0x08,
+  0x6d, 0x5f, 0x08, 0x65, 0x20, 0x61, 0x73, 0x20, 0x74, 0x68, 0x65, 0x20,
+  0x64, 0x61, 0x74, 0x61, 0x62, 0x61, 0x73, 0x65, 0x20, 0x74, 0x6f, 0x20,
+  0x63, 0x6f, 0x6d, 0x70, 0x61, 0x72, 0x65, 0x20, 0x73, 0x74, 0x61, 0x72,
+  0x73, 0x20, 0x61, 0x67, 0x61, 0x69, 0x6e, 0x73, 0x74, 0x2e, 0x0a, 0x0a,
+  0x0a, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x2d, 0x08, 0x2d, 0x2d,
+  0x08, 0x2d, 0x68, 0x08, 0x68, 0x65, 0x08, 0x65, 0x6c, 0x08, 0x6c, 0x70,
+  0x08, 0x70, 0x20, 0x50, 0x72, 0x69, 0x6e, 0x74, 0x73, 0x20, 0x20, 0x74,
+  0x68, 0x65, 0x20, 0x20, 0x63, 0x6f, 0x6e, 0x74, 0x65, 0x6e, 0x74, 0x73,
+  0x20, 0x6f, 0x66, 0x20, 0x74, 0x68, 0x65, 0x20, 0x6d, 0x61, 0x6e, 0x75,
+  0x61, 0x6c, 0x20, 0x65, 0x6e, 0x74, 0x72, 0x79, 0x20, 0x66, 0x6f, 0x72,
+  0x20, 0x74, 0x68, 0x65, 0x20, 0x63, 0x6f, 0x6d, 0x6d, 0x61, 0x6e, 0x64,
+  0x20, 0x74, 0x6f, 0x20, 0x74, 0x68, 0x65, 0x0a, 0x20, 0x20, 0x20, 0x20,
+  0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x74, 0x65,
+  0x72, 0x6d, 0x69, 0x6e, 0x61, 0x6c, 0x2e, 0x0a, 0x0a, 0x0a, 0x53, 0x08,
+  0x53, 0x45, 0x08, 0x45, 0x45, 0x08, 0x45, 0x20, 0x41, 0x08, 0x41, 0x4c,
+  0x08, 0x4c, 0x53, 0x08, 0x53, 0x4f, 0x08, 0x4f, 0x0a, 0x20, 0x20, 0x20,
+  0x20, 0x20, 0x20, 0x20, 0x64, 0x61, 0x74, 0x61, 0x62, 0x61, 0x73, 0x65,
+  0x28, 0x33, 0x29, 0x0a, 0x0a, 0x0a, 0x0a, 0x20, 0x20, 0x20, 0x20, 0x20,
+  0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20,
+  0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20,
+  0x20, 0x20, 0x30, 0x36, 0x20, 0x4e, 0x6f, 0x76, 0x65, 0x6d, 0x62, 0x65,
+  0x72, 0x20, 0x32, 0x30, 0x32, 0x31, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20,
+  0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20,
+  0x20, 0x20, 0x50, 0x49, 0x50, 0x45, 0x4c, 0x49, 0x4e, 0x45, 0x28, 0x33,
+  0x29, 0x0a
+};
+unsigned int documentation_pipeline_txt_len = 15710;
diff --git a/src/centroiders.cpp b/src/centroiders.cpp
index aec56f50..38c6f716 100644
--- a/src/centroiders.cpp
+++ b/src/centroiders.cpp
@@ -11,11 +11,11 @@
 
 #include <unordered_set>
 #include <string.h>
+#include <cassert>
 
 namespace lost {
 
-// DUMMY
-
+// DUMMYS
 std::vector<Star> DummyCentroidAlgorithm::Go(unsigned char *image, int imageWidth, int imageHeight) const {
     std::vector<Star> result;
 
@@ -26,7 +26,7 @@ std::vector<Star> DummyCentroidAlgorithm::Go(unsigned char *image, int imageWidt
     return result;
 }
 
-// a poorly designed thresholding algorithm
+// UNUSED: a poorly designed thresholding algorithm
 int BadThreshold(unsigned char *image, int imageWidth, int imageHeight) {
     //loop through entire array, find sum of magnitudes
     long totalMag = 0;
@@ -36,7 +36,7 @@ int BadThreshold(unsigned char *image, int imageWidth, int imageHeight) {
     return (((totalMag/(imageHeight * imageWidth)) + 1) * 15) / 10;
 }
 
-// a more sophisticated thresholding algorithm, not tailored to star images
+// UNUSED: a more sophisticated thresholding algorithm, not tailored to star images
 int OtsusThreshold(unsigned char *image, int imageWidth, int imageHeight) {
     // code here, duh
     long total = imageWidth * imageHeight;
@@ -76,7 +76,7 @@ int OtsusThreshold(unsigned char *image, int imageWidth, int imageHeight) {
     return level;
 }
 
-// a simple, but well tested thresholding algorithm that works well with star images
+// UNUSED: a simple, but well tested thresholding algorithm that works well with star images.
 int BasicThreshold(unsigned char *image, int imageWidth, int imageHeight) {
     unsigned long totalMag = 0;
     float std = 0;
@@ -92,7 +92,9 @@ int BasicThreshold(unsigned char *image, int imageWidth, int imageHeight) {
     return mean + (std * 5);
 }
 
-// basic thresholding, but do it faster (trade off of some accuracy?)
+// UNUSED: Accepts an array of brightnesses and image dimensions, and returns the 
+// threshold brightness for the entire image, which is defined as 5 standard deviations
+// above the mean.
 int BasicThresholdOnePass(unsigned char *image, int imageWidth, int imageHeight) {
     unsigned long totalMag = 0;
     float std = 0;
@@ -105,9 +107,98 @@ int BasicThresholdOnePass(unsigned char *image, int imageWidth, int imageHeight)
     float mean = totalMag / totalPixels;
     float variance = (sq_totalMag / totalPixels) - (mean * mean);
     std = std::sqrt(variance);
-    return mean + (std * 5);
+    return std::round(mean + (std * 5));
+}
+
+//                          *****START OF COG ALGORITHM*****
+
+// This algorithm takes an image and finds all "centroids" or potential stars in it. It divides
+// the image into a square grid, calculates the threshold brightness of each subsection, or "box",
+// and uses that information to find the centroids. A threshold is defined as 5 standard deviations
+// above the mean brightness of pixels.
+
+// Commonly used terms:
+    // box: A subsection in the subdivision scheme
+    // subdivision scheme: The square grid that contains the boxes the image is divided into. Each
+        // box can be assigned an index in this scheme, which follows row-major order.
+    // subdivisions: The number of slices the image is sliced into on each side. The square of
+        // this quantity indicates the number of boxes.
+    // leftover: When doing this division, we often cannot give each box the same number of
+        // rows/columns to each box. This quantity tell us how many rows/columns in the subdivision
+        // scheme will have 1 extra row/column, and these always start with the first rows/columns.
+    // div: The minimum rows/columns each box will have.
+    // For leftover and div, "horizontal" refers to rows and "vertical" refers to columns
+
+// By default, this algorithm ensures that regardless of the subdivisions entered, the number of
+// pixels in each subdivision is imageWidth*imageHeight <= size <= 100 to ensure that enough
+// pixles will be sampled in each subdivision
+
+// Accepts an index in the subdivision scheme, and a horizontal/vertical leftover and div
+// This method uses these quantities to find the first row/column index in the actual image
+// that "i" references.
+int StartOfSubdivision(int i, int leftover, int div) {
+    if(i < leftover) {
+        return i * (div + 1);
+    } else {
+        return leftover * (div + 1) + (i - leftover) * div;
+    }
+}
+
+// Refer to definition for details
+long FindSubdivision(long i, int imageWidth, int imageHeight, int subdivisions);
+
+
+// Accepts a subdivsion, or "box" number, the image's brightness array and associated dimensions, 
+// and the subdivisions.
+// Returns the threshold for the corresponding box.
+int LocalBasicThreshold(int box, unsigned char *image, int imageWidth, int imageHeight, 
+        int subdivisions) {
+
+    int horizontalDiv = imageHeight / subdivisions;
+    int verticalDiv = imageWidth / subdivisions;
+    int horizontalLeftover = imageHeight % subdivisions;
+    int verticalLeftover = imageWidth % subdivisions;
+    int row = box / subdivisions; // Finds the current row in the subdivision scheme
+    int col = box % subdivisions; // Finds the current column in the subdivision scheme
+    double average = 0;
+    double squareSum = 0;
+    long count = 0;
+
+    // Runs through "box" in row-major order
+    for(long i = StartOfSubdivision(row, horizontalLeftover, horizontalDiv); 
+            i < StartOfSubdivision(row + 1, horizontalLeftover, horizontalDiv); i++) {
+        for(long j = StartOfSubdivision(col, verticalLeftover, verticalDiv); 
+                j < StartOfSubdivision(col + 1, verticalLeftover, verticalDiv); j++) {
+            average += image[i * imageWidth + j];
+            squareSum += image[i * imageWidth + j] * image[i * imageWidth + j];
+            count++;
+
+            // Checks for Error
+            assert(FindSubdivision(i*imageWidth+j, imageWidth, imageHeight, subdivisions) == box);
+        }
+    }
+
+    average /= count;
+    return average + (5 * std::sqrt((squareSum - count * average * average) / (count - 1)));
 }
 
+// Accepts the image's brightness array and dimensions, and the subdivisions, and returns
+// a vector with the threshold for each "box" in row-major order
+std::vector<int> LocalThresholding(unsigned char *image, int imageWidth, int imageHeight, 
+        int subdivisions) {
+    
+    std::vector<int> thresholds;
+    for(int i = 0; i < subdivisions * subdivisions; i++) {
+        thresholds.push_back(LocalBasicThreshold(i, image, imageWidth, imageHeight, 
+                subdivisions));
+    }
+
+    return thresholds;
+}
+
+// Used in function CenterOfGravityAlgorithm:Go, and is useful for keeping track of
+// star dimensions and characteristics, as well as the database of thresholds among
+// other quantities relating to the image
 struct CentroidParams {
     float yCoordMagSum; 
     float xCoordMagSum;
@@ -116,84 +207,177 @@ struct CentroidParams {
     int xMax;
     int yMin;
     int yMax;
-    int cutoff;
+    int magnitude;
     bool isValid;
-    std::unordered_set<int> checkedIndices;
 };
 
-//recursive helper here
-void CogHelper(CentroidParams &p, long i, unsigned char *image, int imageWidth, int imageHeight) {
-    
-    if (i >= 0 && i < imageWidth * imageHeight && image[i] >= p.cutoff && p.checkedIndices.count(i) == 0) {
-        //check if pixel is on the edge of the image, if it is, we dont want to centroid this star
-        if (i % imageWidth == 0 || i % imageWidth == imageWidth - 1 || i / imageWidth == 0 || i / imageWidth == imageHeight - 1) {
-            p.isValid = false;
-        }
-        p.checkedIndices.insert(i);
-        if (i % imageWidth > p.xMax) {
-            p.xMax = i % imageWidth;
-        } else if (i % imageWidth < p.xMin) {
-            p.xMin = i % imageWidth;
-        }
-        if (i / imageWidth > p.yMax) {
-            p.yMax = i / imageWidth;
-        } else if (i / imageWidth < p.yMin) {
-            p.yMin = i / imageWidth;
-        }
-        p.magSum += image[i];
-        p.xCoordMagSum += ((i % imageWidth)) * image[i];
-        p.yCoordMagSum += ((i / imageWidth)) * image[i];
-        if(i % imageWidth != imageWidth - 1) {
-            CogHelper(p, i + 1, image, imageWidth, imageHeight);
-        }
-        if (i % imageWidth != 0) {
-            CogHelper(p, i - 1, image, imageWidth, imageHeight);
-        }
-        CogHelper(p, i + imageWidth, image, imageWidth, imageHeight);
-        CogHelper(p, i - imageWidth, image, imageWidth, imageHeight);
+// Accepts the row/column of an index on the image, the imageWidth/imageHeight, the subdivisions
+// and the horizontal/vertical div and leftover
+// Returns the index of the row/column in the subdivision scheme for the corresponding "i".
+// NOTE: This function is the inverse of the StartOfSubdivision function in a way that
+// RowOrColumn(StartOfSubdivision(x)) = x for any given row/column index "x" in the subdivision 
+// scheme, but StartOfSubdivision(RowOrColumn(x)) only equals x if x = StartOfSubdivision(y),
+// for any given row/column index "y" in the subdivision scheme 
+long RowOrColumn(long i, int leftover, int div) {
+    if(i < (div + 1) * leftover) {
+        return i / (div + 1);
+    } else {
+        return leftover + (i - (div + 1) * leftover) / (div);
     }
 }
 
-std::vector<Star> CenterOfGravityAlgorithm::Go(unsigned char *image, int imageWidth, int imageHeight) const {
-    CentroidParams p;
-    
-    std::vector<Star> result;
+// Accepts an index in the image, its dimensions and the subdivisions, and returns the 
+// corresponding "box" number that the index "i" is in
+long FindSubdivision(long i, int imageWidth, int imageHeight, int subdivisions) {
+    long row = RowOrColumn(i / imageWidth, imageHeight % subdivisions, imageHeight / subdivisions);
+    long col = RowOrColumn(i % imageWidth, imageWidth % subdivisions, imageWidth / subdivisions);
+    return  row * subdivisions + col;
+}
 
-    p.cutoff = BasicThreshold(image, imageWidth, imageHeight);
-    for (long i = 0; i < imageHeight * imageWidth; i++) {
-        if (image[i] >= p.cutoff && p.checkedIndices.count(i) == 0) {
 
-            //iterate over pixels that are part of the star
-            int xDiameter = 0; //radius of current star
-            int yDiameter = 0;
-            p.yCoordMagSum = 0; //y coordinate of current star
-            p.xCoordMagSum = 0; //x coordinate of current star
-            p.magSum = 0; //sum of magnitudes of current star
+// Accepts an array of the image's brightnesses, and the image's dimensions, and finds all
+// stars in the image and returns the stars as an array
+std::vector<Star> CenterOfGravityAlgorithm::Go(unsigned char *image, int imageWidth, int imageHeight) const {
+    
+    // Program will use divisions to represent the subdivisions
+    int divisions = subdivisions;
+    int min = 0;
+    if(divisions < 1) {
+        divisions = 1;
+    }
+    if(imageWidth > imageHeight) {
+        min = imageWidth;
+    } else {
+        min = imageHeight;
+    }
+    if(min / subdivisions < 10) {
+        divisions = min / 10;
+    }
+    // Make an array-map of thresholds
+    std::vector<int> localCutoff = LocalThresholding(image, imageWidth, imageHeight, divisions);
 
-            p.xMax = i % imageWidth;
-            p.xMin = i % imageWidth;
-            p.yMax = i / imageWidth;
-            p.yMin = i / imageWidth;
-            p.isValid = true;
+    // Tells us if certian numbers in the below array are part of the same component
+    std::unordered_map<int, int> equivalencies;
+    
+    // make an array with the same dimensions of the image, but it shows connected components using numbers
+    unsigned char *stars = (unsigned char *) std::malloc(imageWidth * imageHeight * sizeof(unsigned char));
+    stars[0] = (image[0] >= localCutoff.at(0)) ? 1 : 0;
+    int L = stars[0];
+
+    // Initial labeling of centroids
+    for(long i = 1; i < imageHeight * imageWidth; i++) {
+        // This is specific to the centroiding algo, which tests if this is even part of a centroid
+        if(image[i] >= localCutoff.at(FindSubdivision(i, imageWidth, imageHeight, divisions))) {
+
+            // The indicies of the entries to the left and above i
+            int up = i - imageWidth;
+            int left = i - 1;
+
+            // Tests to see if the upper or left entry is a valid component (part of a star aka it was initialized
+            // with a L value at some point)
+            bool leftEq = stars[left] != 0;
+            bool upEq = stars[up] != 0;
+
+            if(i / imageWidth == 0) { // If i is part of a top pixel, test only the left pixel
+                if(leftEq) { // If the left pixel is part of a centroid, it must be part of the same star as i, if not, mark with new L value
+                    stars[i] = stars[left];
+                } else {
+                    stars[i] = ++L;
+                }
+            } else if(i % imageWidth == 0) { // If i is part of a left pixel, test only the upper pixel
+                if(upEq) { // If the upper pixel is part of a centroid, it must be part of the same star as i, if not, mark with new L value
+                    stars[i] = stars[up];
+                } else {
+                    stars[i] = ++L;
+                }
+            } else { // Tests for general case
+                if(leftEq && upEq && stars[left] == stars[up]) { // If the top and left pixels are part of centroid with the same L value, i is connected to them with the same L value
+                    stars[i] = stars[left];
+                } else if(leftEq && upEq && stars[left] != stars[up]) { // The above, but if the left and top pixels have different L values, those different values are also part of the same centroid
+                    stars[i] = std::min(stars[left], stars[up]);
+                    equivalencies.insert(std::pair<int, int>(int(std::max(stars[left], stars[up])), int(stars[i])));
+                    assert(equivalencies.find(stars[i]) == equivalencies.end());
+                } else if(leftEq) { // From here, we get a copy of the first two if/else if statements
+                    stars[i] = stars[left];
+                } else if(upEq) { 
+                    stars[i] = stars[up];
+                } else {
+                    stars[i] = ++L;
+                }
+            }
+        }
+    }
 
-            int sizeBefore = p.checkedIndices.size();
+    // Get statistics of each star. This is when we process the above info
+    // into groups based on the pixels having the same number (or equivalent numebers via the map)
+    // params is a mapping of these centroid numbers (L values) to each "group" of pixels with statistics
+    // shown in Centroid params.
+    std::unordered_map<int, CentroidParams> params; // Star # to param
+    for(int i = 0; i < imageWidth * imageHeight; i++) {
+        if(stars[i] != 0) {
+            int starNumber = equivalencies.find(stars[i]) == equivalencies.end() ? 
+                    stars[i] : equivalencies.find(stars[i]) -> second;
+            if(params.find(starNumber) == params.end()) { // If the entry with the L value given at stars[i] is not yet in params, then initialze one
+                CentroidParams p;
+                p.magnitude = 0;
+                p.magSum = 0;
+                p.xCoordMagSum = 0;
+                p.yCoordMagSum = 0;
+                p.xMax = 0;
+                p.xMin = imageWidth;
+                p.yMax = 0;
+                p.yMin = imageHeight;
+                p.isValid = true;
+                params.insert(std::pair<int, CentroidParams>(starNumber, p));
+            }
+            // Obtain and update the statistics for the centroid corresponding to the L value at stars[i] or the equivalent L value
+            CentroidParams *centroid_ptr = &params.at(starNumber);
+            int row = i / imageWidth;
+            int col = i % imageWidth;
+            centroid_ptr -> xCoordMagSum += col * image[i];
+            centroid_ptr -> yCoordMagSum += row * image[i];
+            centroid_ptr -> magnitude++;
+            centroid_ptr -> magSum += image[i];
+            if(col > centroid_ptr -> xMax) {
+                centroid_ptr -> xMax = col;
+            }
+            if(col < centroid_ptr -> xMin) {
+                centroid_ptr -> xMin = col;
+            }
+            if(row > centroid_ptr -> yMax) {
+                centroid_ptr -> yMax = row;
+            }
+            if(row < centroid_ptr -> yMin) {
+                centroid_ptr -> yMin = row;
+            }
+            if (i % imageWidth == 0 || i % imageWidth == imageWidth - 1 || i / imageWidth == 0 || 
+                i / imageWidth == imageHeight - 1) {
+                centroid_ptr -> isValid = false;
+            }
 
-            CogHelper(p, i, image, imageWidth, imageHeight);
-            xDiameter = (p.xMax - p.xMin) + 1;
-            yDiameter = (p.yMax - p.yMin) + 1;
+        }
+   }
 
-            //use the sums to finish CoG equation and add stars to the result
-            float xCoord = (p.xCoordMagSum / (p.magSum * 1.0));      
+    // Now we actually make stars. This is the last step, and is when we validate each CentroidParam,
+    // make sure it is a valid centroid and that the param entry is a valid one (Not 0). Then we use
+    // our CentroidParams to initialize an actual centroid (Star)
+    std::vector<Star> result;
+    for(auto itr = params.begin(); itr != params.end(); itr++) {
+        if(itr -> second.isValid && itr -> first != 0) {
+            CentroidParams p = itr -> second;
+            float xRadius = p.xMax - p.xMin + 1;
+            float yRadius = p.yMax - p.yMin + 1;
+            float xCoord = (p.xCoordMagSum / (p.magSum * 1.0));
             float yCoord = (p.yCoordMagSum / (p.magSum * 1.0));
-
-            if (p.isValid) {
-                result.push_back(Star(xCoord + 0.5f, yCoord + 0.5f, ((float)(xDiameter))/2.0f, ((float)(yDiameter))/2.0f, p.checkedIndices.size() - sizeBefore));
-            }
+            result.push_back(Star(xCoord + 0.5f, yCoord + 0.5f, xRadius / 2.0f, yRadius / 2.0f, p.magnitude));
         }
     }
+
     return result;
 }
 
+//                          *****END OF COG ALGORITHM*****
+
 //Determines how accurate and how much iteration is done by the IWCoG algorithm,
 //smaller means more accurate and more iterations.
 float iWCoGMinChange = 0.0002;
@@ -213,7 +397,8 @@ struct IWCoGParams {
 void IWCoGHelper(IWCoGParams &p, long i, unsigned char *image, int imageWidth, int imageHeight, std::vector<int> &starIndices) {
     if (i >= 0 && i < imageWidth * imageHeight && image[i] >= p.cutoff && p.checkedIndices.count(i) == 0) {
         //check if pixel is on the edge of the image, if it is, we dont want to centroid this star
-        if (i % imageWidth == 0 || i % imageWidth == imageWidth - 1 || i / imageWidth == 0 || i / imageWidth == imageHeight - 1) {
+        if (i % imageWidth == 0 || i % imageWidth == imageWidth - 1 || i / imageWidth == 0 
+                || i / imageWidth == imageHeight - 1) {
             p.isValid = false;
         }
         p.checkedIndices.insert(i);
diff --git a/src/centroiders.hpp b/src/centroiders.hpp
index 5b6c2477..98e0b8aa 100644
--- a/src/centroiders.hpp
+++ b/src/centroiders.hpp
@@ -24,8 +24,10 @@ class DummyCentroidAlgorithm: public CentroidAlgorithm {
 
 class CenterOfGravityAlgorithm : public CentroidAlgorithm {
     public:
-        CenterOfGravityAlgorithm() { };
+        CenterOfGravityAlgorithm(int subdivisions) : subdivisions(subdivisions) { };
         Stars Go(unsigned char *image, int imageWidth, int imageHeight) const override;
+    private:
+        int subdivisions;
 };
 
 class IterativeWeightedCenterOfGravityAlgorithm : public CentroidAlgorithm {
diff --git a/src/io.cpp b/src/io.cpp
index 7920514d..6f59489c 100644
--- a/src/io.cpp
+++ b/src/io.cpp
@@ -268,7 +268,8 @@ CentroidAlgorithm *DummyCentroidAlgorithmPrompt() {
 }
 
 CentroidAlgorithm *CoGCentroidAlgorithmPrompt() {
-    return new CenterOfGravityAlgorithm();
+    int subdivisions = Prompt<int>("How many subdivisions to use");
+    return new CenterOfGravityAlgorithm(subdivisions);
 }
 
 CentroidAlgorithm *IWCoGCentroidAlgorithmPrompt() {
diff --git a/test/centroid.cpp b/test/centroid.cpp
new file mode 100644
index 00000000..277a0b7c
--- /dev/null
+++ b/test/centroid.cpp
@@ -0,0 +1,56 @@
+#include <catch.hpp>
+
+#include <math.h>
+#include <iostream>
+
+namespace lost {
+    int RowOrColumn(long i, int leftover, int div);
+    int FindSubdivision(long i, int imageWidth, int imageHeight, int subdivisions);
+    int StartOfSubdivision(int i, int leftover, int div);
+}
+
+
+TEST_CASE("Testing Start and End Rows") {
+    int row = 0;
+    int horizontalLeftover = 5;
+    int horizontalDiv = 10;
+    CHECK(lost::StartOfSubdivision(row, horizontalLeftover, horizontalDiv) == 0);
+    CHECK(lost::StartOfSubdivision(row + 1, horizontalLeftover, horizontalDiv) == 11);
+}
+
+TEST_CASE("Testing Start and End Columns") {
+    int col = 0;
+    int verticalLeftover = 5;
+    int verticalDiv = 10;
+    CHECK(lost::StartOfSubdivision(col, verticalLeftover, verticalDiv) == 0);
+    CHECK(lost::StartOfSubdivision(col + 1, verticalLeftover, verticalDiv) == 11);
+}
+
+TEST_CASE("Correct Row: 4th Row") {
+    CHECK(lost::RowOrColumn(33795 / 1024, 1024 % 100, 1024 / 100) == 3);
+}
+
+TEST_CASE("Correct Row: 27th Row") {
+    CHECK(lost::RowOrColumn((24 * 1024 * 11 + 10 * 2 * 1024 + 20) / 1024, 1024 % 100, 1024 / 100) == 26);
+}
+
+TEST_CASE("Correct Row: Last Row 1") {
+    CHECK(lost::RowOrColumn((1024 * 1024 - 1) / 1024, 1024 % 100, 1024 / 100) == 99);
+}
+
+TEST_CASE("Correct Box: Last Subdivision") {
+    CHECK(lost::FindSubdivision(1024 * 1024 - 1, 1024, 1024, 1024) == 1024 * 1024 - 1);
+}
+
+TEST_CASE("Testing Inverse Conjecture") {
+    int size = 1024;
+    int subdivisions = 10;
+    int leftover = size % subdivisions;
+    int div = size / subdivisions;
+    for(int i = 0; i < subdivisions; i++) {
+        int x = lost::StartOfSubdivision(i, leftover, div);
+        CHECK(lost::RowOrColumn(x, leftover, div) == i);
+        CHECK(lost::StartOfSubdivision(lost::RowOrColumn(x, leftover, div), leftover, div) == x);
+    }
+}
+