Implementing Stickers on an Image in Phimpme

One feature we implemented in the Phimpme photo editing application is to enable users to add stickers on top of the image. In this blog, I will explain how stickers are implemented in Phimpme.

Features of Stickers

  • Users can resize the stickers.
  • Users can place the stickers wherever in the canvas.

Step.1-Storing the Stickers in assets folder

In Phimpme I stored the stickers in the assets folder. To distribute the stickers in different categories I made different folders according to the categories namely type1, type2, type3, type4 and so on.  

Displaying stickers

We used onBindViewHolder to Display the stickers in different categories like:

  • Facial
  • Express
  • Objects
  • Comments
  • Wishes
  • Emojis
  • Hashtags

String path will get the position of the particular type of stickers collection. This type is then loaded to the ImageLoader with the specific icon associating with the types.   

@Override
public void onBindViewHolder(mRecyclerAdapter.mViewHolder holder, final int position) {

   String path = pathList.get(position);
       ImageLoader.getInstance().displayImage("assets://" + path,holder.icon, imageOption);
       holder.itemView.setTag(path);
       holder.title.setText("");

   int size = (int) getActivity().getResources().getDimension(R.dimen.icon_item_image_size_filter_preview);
   LinearLayout.LayoutParams layoutParams = new LinearLayout.LayoutParams(size,size);
   holder.icon.setLayoutParams(layoutParams);

   holder.itemView.setOnClickListener(new View.OnClickListener() {
       @Override
       public void onClick(View v) {
           String data = (String) v.getTag();
           selectedStickerItem(data);
       }
   });
}

Step.2- Applying a sticker on the image

When a particular sticker is selected selectedStickerItem() function is called.This function calls StickerView class to add the Bitmap on the image. It sends the path of the sticker as a parameter.  

public void selectedStickerItem(String path) {
   mStickerView.addBitImage(getImageFromAssetsFile(path));
}

In StickerView class the image of the sticker is then converted into a Bitmap. It creates an object(item) of StickerItem class. This object calls the init function, which handles the size of the sticker and the placement of the sticker on the image.

public void addBitImage(final Bitmap addBit) {
   StickerItem item = new StickerItem(this.getContext());
   item.init(addBit, this);
   if (currentItem != null) {
       currentItem.isDrawHelpTool = false;
   }
   bank.put(++imageCount, item);
   this.invalidate();
}

Step.3-Resizing the Sticker in the canvas

A bitmap or any image has two axes namely x and y. We can resize the image using matrix calculation.

float c_x = dstRect.centerX();
float c_y = dstRect.centerY();

float x = this.detectRotateRect.centerX();
float y = this.detectRotateRect.centerY();

We then calculate the source length and the current length:

float srcLen = (float) Math.sqrt(xa * xa + ya * ya);
float curLen = (float) Math.sqrt(xb * xb + yb * yb);

Then we calculate the scale. This is required to calculate the zoom ratio.

float scale = curLen / srcLen;

We need to rescale the bitmap. That is if the user rotates the sticker or zoom in or zoom out the sticker. A helpbox surrounds the stickers showing the actual size of the sticker. This helpbox which is rectangular shape helps in resizing the sticker.

RectUtil.scaleRect(this.dstRect, scale);// Zoom destination rectangle

// Recalculate the Toolbox coordinates
helpBox.set(dstRect);
updateHelpBoxRect();// Recalculate
rotateRect.offsetTo(helpBox.right - BUTTON_WIDTH, helpBox.bottom
       - BUTTON_WIDTH);
deleteRect.offsetTo(helpBox.left - BUTTON_WIDTH, helpBox.top
       - BUTTON_WIDTH);

detectRotateRect.offsetTo(helpBox.right - BUTTON_WIDTH, helpBox.bottom
       - BUTTON_WIDTH);
detectDeleteRect.offsetTo(helpBox.left - BUTTON_WIDTH, helpBox.top
       - BUTTON_WIDTH);

Conclusion

In Phimpme a user can now place the sticker on top of the image. Resize the sticker, that is Zoom in the image or zoom out of the image. Move the image around the canvas. This will give users the flexibility to add multiple stickers on the image.

Github

Resources

Integrating OpenCV for Native Image Processing in Phimpme Android

OpenCV is an open source computer vision library written in C and C++. It has many pre-built image processing functions for all kinds of purposes. The filters and image enhancing functions which we implemented in Phimpme are not fully optimized. So we decided to integrate the Android SDK of OpenCV in the Phimpme Android application.

For integrating OpenCV in the application, the files inside the OpenCV Android SDK have to be properly placed inside the project. The build and make files of the project have to be configured correspondingly.

Here, in this post, I will mention how we fully integrated OpenCV Android SDK and configured the Phimpme project.

Setting Up

First, we downloaded the OpenCV-Android-SDK zip from the official release page here.

Now we extracted the OpenCV-Android-SDK.zip file to navigated to SDK folder to see that there are three folders inside it. etc, Java and native.

All the build files are present inside the native directory and are necessarily copied to our project. The java directory inside the SDK folder is an external gradle module which has to imported and added as a dependency to our project.

So we copied all the files from jni directory of SDK folder inside OpenCV-Android-SDK to jni directory of the Phimpme project inside main. Similarly copied the 3rdparty directory into the main folder of the Phimpme project. Libs folder should also be copied into the main folder of the Phimpme but it has to be renamed to jniLibs. The project structure can be viewed in the below image.

Adding Module to Project

Now we headed to Android Studio and right clicked on the app in the project view, to add a new module. In that window select import Gradle project and browse to the java folder inside the SDK folder of OpenCV-Android-SDK as shown in figures.

Now we opened the build.gradle file of app level (not project level) and added the following line as a dependency.

  compile project(':openCVLibrary320')

Now open the build.gradle inside the openCVLibrary320 external module and change the platform tools version and  SDK versions.

Configuring Native Build Files

We removed all files related to cmake be we use ndk-build to compile native code. After removing the cmake files, added following lines in the application.mk file

APP_OPTIM := release
APP_ABI := all
APP_STL := gnustl_static
APP_CPPFLAGS := -frtti -fexceptions
APP_PLATFORM := android-25

Now we further added the following lines to the top of Android.mk file

OPENCV_INSTALL_MODULES:=on
OPENCV_CAMERA_MODULES:=on
OPENCV_LIB_TYPE := STATIC
include $(LOCAL_PATH)/OpenCV.mk

The third line here is a flag indicating that the library has to be static and there is no need for external OpenCVLoader application.

Finally, find this line

OPENCV_LIBS_DIR:=$(OPENCV_THIS_DIR)/../libs/$(OPENCV_TARGET_ARCH_ABI)

in OpenCV.mk file and replace it with

OPENCV_LIBS_DIR:=$(OPENCV_THIS_DIR)/../jniLibs/$(OPENCV_TARGET_ARCH_ABI)

And finally, add the following lines to java part. So that the OpenCV is initialized and linked to application

static {
   if (!OpenCVLoader.initDebug()) {
       Log.e( TAG + " - Error", "Unable to load OpenCV");
   } else {
       System.loadLibrary("modulename_present_in_Android.mk");
   }
}

With this, the integration of OpenCV and the configuration of the project is completed. Remove the build directories i.e. .build and .externalNativeBuild directories inside app folder for a fresh build so that you don’t face any wrong build error.

Resources

Passing Java Bitmap Object to Native for Image Processing and Getting it back in Phimpme Android

To perform any image processing operations on an image, we must have an image object in native part like we have a Bitmap object in Java. We cannot just pass the image bitmap object directly as an argument to native function because ‘Bitmap’ is a java object and C/C++ cannot interpret it directly as an image. So, here I’ll discuss a method to send java Bitmap object to Native part for performing image processing operations on it, which we implemented in the image editor of Phimpme Android Image Application.

C/C++ cannot interpret java bitmap object. So, we have to find the pixels of the java bitmap object and send them to native part to create a native bitmap over there.

In Phimpme, we used a “struct” data structure in C to represent native bitmap. An image has three color channels red, green, blue. We consider alpha channel(transparency) for an argb8888 type image. But in Phimpme, we considered only three channels as it is enough to manipulate these channels to implement the edit functions, which we used in the Editor of Phimpme.

We defined a struct, type-defined as NativeBitmap with attributes corresponding to all the three channels. We defined this in the nativebitmap.h header file in the jni/ folder of Phimpme so that we can include this header file in c files in which we needed to use a NativeBitmap struct.

#ifndef NATIVEBITMAP
#define NATIVEBITMAP
#endif
typedef struct {
  unsigned int width;
  unsigned int height;
  unsigned int redWidth;
  unsigned int redHeight;
  unsigned int greenWidth;
  unsigned int greenHeight;
  unsigned int blueWidth;
  unsigned int blueHeight;
  unsigned char* red;
  unsigned char* green;
  unsigned char* blue;
} NativeBitmap;

void deleteBitmap(NativeBitmap* bitmap);
int initBitmapMemory(NativeBitmap* bitmap, int width, int height);

As I explained in my previous post here on introduction to flow of native functions in Phimpme-Android, we defined the native functions with necessary arguments in Java part of Phimpme. We needed the image bitmap to be sent to the native part of the Phimpme application. So the argument in the function should have been java Bitmap object. But as mentioned earlier, the C code cannot interpret this java bitmap object directly as an image. So we created a function for getting pixels from a bitmap object in the Java class of Phimpme application. This function returns an array of unsigned integers which correspond to the pixels of a particular row of the image bitmap. The array of integers can be interpreted by C, so we can send this array of integers to native part and create a receiving native function to create NativeBitmap.

We performed image processing operations like enhancing and applying filters on this NativeBitmap and after the processing is done, we sent the array of integers corresponding to a row of the image bitmap and constructed the Java Bitmap Object using those received arrays in java.

The integers present in the array correspond to the color value of a particular pixel of the image bitmap. We used this color value to get red, green and blue values in native part of the Phimpme application.

Java Implementation for getting pixels from the bitmap, sending to and receiving from native is shown below.

private static void sendBitmapToNative(NativeBitmap bitmap) {
   int width = bitmap.getWidth();
   int height = bitmap.getHeight();
   nativeInitBitmap(width, height);
   int[] pixels = new int[width];
   for (int y = 0; y < height; y++) {
       bitmap.getPixels(pixels, 0, width, 0, y, width, 1); 
                    //gets pixels of the y’th row
       nativeSetBitmapRow(y, pixels);
   }
}
private static Bitmap getBitmapFromNative(NativeBitmap bitmap) {
   bitmap = Bitmap.createBitmap(srcBitmap.getWidth(), srcBitmap.getHeight(), srcBitmap.getConfig());
   int[] pixels = new int[width];
   for (int y = 0; y < height; y++) {
       nativeGetBitmapRow(y, pixels);
       bitmap.setPixels(pixels, 0, width, 0, y, width, 1);
   }
   return bitmap;
}

The native functions which are defined in Java part have to be linked to native functions. So they have to be created with proper function name in main.c (JNI) file of the Phimpme application. We included nativebitmap.h in main.c so that we can use NativeBitmap struct which is defined in nativebitmap.h.
The main functions which do the actual work related to converting integer array received from java part to NativeBitmap and converting back to an integer array of color values of pixels in rows of image bitmap are present in nativebitamp.c. The main.c file acts as Java Native Interface which helps in linking native functions and java functions in Phimpme Android.

After adding all the JNI functions, the main.c function looks as below.

main.c

static NativeBitmap bitmap;
int Java_org_fossasia_phimpme_PhotoProcessing_nativeInitBitmap(JNIEnv* env, jobject thiz, jint width, jint height) {
  return initBitmapMemory(&bitmap, width, height);  //function present
                                                    // in nativebitmap.c
}

void Java_org_fossasia_phimpme_PhotoProcessing_nativeSetBitmapRow(JNIEnv* env, jobject thiz, jint y, jintArray pixels) {
  int cpixels[bitmap.width];
  (*env)->GetIntArrayRegion(env, pixels, 0, bitmap.width, cpixels);
  setBitmapRowFromIntegers(&bitmap, (int)y, &cpixels);
}

void Java_org_fossasia_phimpme_PhotoProcessing_nativeGetBitmapRow(JNIEnv* env, jobject thiz, jint y, jintArray pixels) {
  int cpixels[bitmap.width];
  getBitmapRowAsIntegers(&bitmap, (int)y, &cpixels);
  (*env)->SetIntArrayRegion(env, pixels, 0, bitmap.width, cpixels);
                    //sending bitmap row as output
}

We now reached the main part of the implementation where we created the functions for storing integer array of color values of pixels in the NativeBitmap struct, which we created in nativebitmap.h of Phimpme Application. The definition of all the functions is present in nativebitmap.h, so we included that header file in the nativebitmap.c for using NativeBitmap struct in the functions. We implemented the functions defined in main.c i.e. initializing bitmap memory, setting bitmap row using integer array, getting bitmap row and a method for deleting native bitmap from memory after completion of processing the image in nativebitmap.c.

The implementation of nativebitmap.c after adding all functions is shown below. A proper explanation is added as comments wherever necessary.

void setBitmapRowFromIntegers(NativeBitmap* bitmap, int y, int* pixels) {
  //y is the number of the row (yth row)
  //pixels is the pointer to integer array which contains color value of a pixel
  unsigned int width = (*bitmap).width;
  register unsigned int i = (width*y) + width - 1;
                                //this represent the absolute                                 //index of the pixel in the image bitmap  
  register unsigned int x;      //this represent the index of the pixel 
                                //in the particular row of image bitmap
  for (x = width; x--; i--) {
          //functions defined above
     (*bitmap).red[i] = red(pixels[x]);
     (*bitmap).green[i] = green(pixels[x]);
     (*bitmap).blue[i] = blue(pixels[x]);
  }
}

void getBitmapRowAsIntegers(NativeBitmap* bitmap, int y, int* pixels) {
  unsigned int width = (*bitmap).width;
  register unsigned int i = (width*y) + width - 1; 
  register unsigned int x;              
  for (x = width; x--; i--) {
          //function defined above
     pixels[x] = rgb((int)(*bitmap).red[i], (int)(*bitmap).green[i], (int)(*bitmap).blue[i]);
  }
}

The native bitmap has to be initialized first before we set pixel values to it and has to be deleted from memory after completion of the processing. The functions for doing these tasks are given below. These functions should be added to nativebitmap.c file.

void deleteBitmap(NativeBitmap* bitmap) {
//free up memory
  freeUnsignedCharArray(&(*bitmap).red);//do same for green and blue
}

int initBitmapMemory(NativeBitmap* bitmap, int width, int height) {
  deleteBitmap(bitmap); 
             //if nativebitmap already has some value it gets removed
  (*bitmap).width = width;
  (*bitmap).height = height;
  int size = width*height;
  (*bitmap).redWidth = width;
  (*bitmap).redHeight = height;
            //assigning memory to the red,green and blue arrays and
            //checking if it succeeded for each step.
  int resultCode = newUnsignedCharArray(size, &(*bitmap).red);
  if (resultCode != MEMORY_OK) return resultCode;
            //repeat the code given above for green and blue colors
}

You can find the values of different color components of the RGB color value and RGB color values from the values of color components using the below functions. Add these functions to the top of the nativebitmap.c file.

int rgb(int red, int green, int blue) {
  return (0xFF << 24) | (red << 16) | (green << 8) | blue;
//Find the color value(int) from the red, green, blue values of a particular //pixel.
}

unsigned char red(int color) {
  return (unsigned char)((color >> 16) & 0xFF);
//Getting the red value form the color value of a particular pixel
}

//for green return this ((color >> 8) & 0xFF)
//for blue return this (color & 0xFF);

Do not forget to define native functions in Java part. As now everything got set up, we can use this in PhotoProcessing.java in the following manner to send Bitmap object to native.

Bitmap input = somebitmap;
if  (bitmap != null) {
    sendBitmapToNative(bitmap);
}

////Do some native processing on native bitmap struct
////Discussed in the next post

Bitmap output = getBitmapFromNative(input);
nativeDeleteBitmap();

Performing image processing operations on the NativeBitmap in the image editor of Phimpme like enhancing the image, applying filters are discussed in next posts.

Resources

Applying Filters on Images using Native Functions in Phimpme Android

In the Phimpme application, the user can apply multiple colorful filters on images captured from application’s camera or already available images on the device. This application of filters on images is performed using native image processing functions. We implemented many filters for enhancing the image. Implementation of few of the filter functions is shown below.

Filters are applied to an image by modifying the color values of pixels in the Phimpme application. This is similar to the implementation of image enhancing functions in the editor of Phimpme. My post on that is available here.

Black and White filter:

Black and white filter can be called as gray scaling the image. In a gray scale image, there will only be a single color channel. If multiple channels are present, the corresponding pixel values in all channels will be same. Here in Phimpme, we have an RGB image. It has 3 color channels. Every pixel has three values. Black and white filter can be implemented by replacing those three different values with the average of those values. The implementation of the function and the resultant image with the comparison is shown below.

void applyBlackAndWhiteFilter(Bitmap* bitmap) {
  register unsigned int i;
  unsigned int length = (*bitmap).width * (*bitmap).height;
  register unsigned char grey;
  unsigned char* red = (*bitmap).red;
  unsigned char* green = (*bitmap).green;
  unsigned char* blue = (*bitmap).blue;
  for (i = length; i--;) {
     grey = (red[i] + green[i] + blue[i]) / 3;
     red[i] = truncate((int) grey);
     green[i] = truncate((int) grey);
     blue[i] = truncate((int) grey);
  }
}

    

Ansel Filter

This Ansel Filter is a monotone filter present in Phimpme which is similar to black and white. Here in this filter, the contrast will be little high and gives the image artistic look. This is achieved in Phimpme by hard overlaying the gray pixel components of the image. The rest is same as the black and white filter. The implementation of hard overlay blending and the Ansel function is shown below with the resultant images.

static unsigned char hardLightLayerPixelComponents(unsigned char maskComponent, unsigned char imageComponent) {

  return (maskComponent > 128) ? 255 - (( (255 - (2 * (maskComponent-128)) ) * (255-imageComponent) )/256) : (2*maskComponent*imageComponent)/256;
}

void applyAnselFilter(Bitmap* bitmap) {
/*initializations*/
  unsigned char br,bg,bb;
  for (i = length; i--; ) {
       grey = (red[i] + green[i] + blue[i]) / 3;
       int eff = hardLightLayerPixelComponents(grey, grey);
       red[i] = truncate(eff);
       green[i] = truncate(eff);
       blue[i] = truncate(eff);
  }
}

    

Sepia Filter

The Sepia Filter in Phimpme results in a monotone image with orangish yellow tone. Its implementation uses pre-defined look up tables(LUTs) for all the three channels. The luminosity of a particular pixel is found out and then the red, green, blue values are found out from the look up tables(LUTs) corresponding to that luminosity. The look up table arrays we used for the sepia effect in Phimpme are given below and the implementation is also shown below.

const unsigned char sepiaRedLut[256] = {24, 24, 25, 26, 27, 28, 29, 30, 30, 30, 31, 32, 33, 34, 35, 36, 37, 37, 38, 38, 39, 40, 41, 42, 43, 43, 44, 45, 46, 47, 47, 48, 49, 50, 50, 51, 52, 53, 54, 55, 56, 57, 57, 58, 58, 59, 60, 61, 62, 63, 64, 64, 65, 66, 67, 68, 69, 70, 71, 71, 72, 72, 73, 74, 75, 76, 77, 78, 78, 79, 80, 81, 82, 83, 84, 85, 85, 86, 87, 88, 89, 89, 90, 91, 92, 93, 93, 94, 95, 96, 97, 97, 98, 99, 100, 101, 102, 102, 103, 104, 105, 106, 107, 108, 109, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 146, 147, 148, 149, 150, 151, 152, 153, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 178, 180, 181, 182, 183, 184, 185, 186, 186, 187, 188, 189, 190, 191, 193, 194, 195, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 255};

const unsigned char sepiaGreenLut[256] = {16, 16, 16, 17, 18, 18, 19, 20, 20, 20, 21, 22, 22, 23, 24, 24, 25, 25, 26, 26, 27, 28, 28, 29, 30, 30, 31, 31, 32, 33, 33, 34, 35, 36, 36, 36, 37, 38, 39, 39, 40, 41, 42, 43, 43, 44, 45, 46, 47, 47, 48, 48, 49, 50, 51, 51, 52, 53, 54, 54, 55, 55, 56, 57, 58, 59, 60, 61, 61, 61, 62, 63, 64, 65, 66, 67, 67, 68, 68, 69, 70, 72, 73, 74, 75, 75, 76, 77, 78, 78, 79, 80, 81, 81, 82, 83, 84, 85, 86, 87, 88, 90, 90, 91, 92, 93, 94, 95, 96, 97, 97, 98, 99, 100, 101, 103, 104, 105, 106, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 122, 123, 123, 124, 125, 127, 128, 129, 130, 131, 132, 132, 134, 135, 136, 137, 138, 139, 141, 141, 142, 144, 145, 146, 147, 148, 149, 150, 151, 152, 154, 155, 156, 157, 158, 160, 160, 161, 162, 163, 165, 166, 167, 168, 169, 170, 171, 173, 174, 175, 176, 177, 178, 179, 180, 182, 183, 184, 185, 187, 188, 189, 189, 191, 192, 193, 194, 196, 197, 198, 198, 200, 201, 202, 203, 205, 206, 207, 208, 209, 210, 211, 212, 213, 215, 216, 217, 218, 219, 220, 221, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 255};

const unsigned char sepiaBlueLut[256] = {5, 5, 5, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9, 9, 10, 10, 11, 11, 11, 11, 12, 12, 13, 13, 14, 14, 14, 14, 15, 15, 16, 16, 17, 17, 17, 18, 18, 19, 20, 20, 21, 21, 21, 22, 22, 23, 23, 24, 25, 25, 26, 27, 28, 28, 29, 29, 30, 31, 31, 31, 32, 33, 33, 34, 35, 36, 37, 38, 38, 39, 39, 40, 41, 42, 43, 43, 44, 45, 46, 47, 47, 48, 49, 50, 51, 52, 53, 53, 54, 55, 56, 57, 58, 59, 60, 60, 61, 62, 63, 65, 66, 67, 67, 68, 69, 70, 72, 73, 74, 75, 75, 76, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 90, 91, 92, 93, 93, 95, 97, 98, 99, 100, 101, 102, 104, 104, 106, 107, 108, 109, 111, 112, 114, 115, 115, 117, 118, 120, 121, 122, 123, 124, 125, 127, 128, 129, 131, 132, 133, 135, 136, 137, 138, 139, 141, 142, 144, 145, 147, 147, 149, 150, 151, 153, 154, 156, 157, 159, 159, 161, 162, 164, 165, 167, 168, 169, 170, 172, 173, 174, 176, 177, 178, 180, 181, 182, 184, 185, 186, 188, 189, 191, 192, 193, 194, 196, 197, 198, 200, 201, 203, 204, 205, 206, 207, 209, 210, 211, 213, 214, 215, 216, 218, 219, 220, 221, 223, 224, 225, 226, 227, 229, 230, 231, 232, 234, 235, 236, 237, 238, 239, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 255};
void applySepia(Bitmap* bitmap){
/*bitmap initializations*/
for (i = length; i--; ) {
  register float r = (float) red[i] / 255;
  register float g = (float) green[i] / 255;
  register float b = (float) blue[i] / 255;
  register float luminosity =  (0.21f * r + 0.72f * g + 0.07 * b) * 255;
      red[i] = truncate((int)( sepiaRedLut[(int)luminosity]));
      green[i] = truncate((int)(sepiaGreenLut[(int)luminosity]));
      blue[i] = truncate((int)(sepiaBlueLut[(int)luminosity]));
  }
}

     

Cyano Filter

As the name suggests this filter adds a cyan tone to the image. For implementing this cyano filter, we first found the black and white value of the pixel and then the ceilingComponent value of the pixels of three color channels. Then the ceilingComponent Values and the gray values are overlayed to give the resultant image. Finding the ceilComponent Values and the filter implementation is shown below.

#define componentCeiling(x) ((x > 255) ? 255 : x)

static unsigned char overlayPixelComponents(unsigned int overlayComponent, unsigned char underlayComponent, float alpha) {
  float underlay = underlayComponent * alpha;
  return (unsigned char)((underlay / 255) * (underlay + ((2.0f * overlayComponent) / 255) * (255 - underlay)));

}

void applyCyano(Bitmap* bitmapl) {
  //Cache to local variables
//Bitamp initialization
  register unsigned int i;
  register unsigned char grey, r, g, b;
  for (i = length; i--;) {
     grey = ((red[i] * 0.222f) + (green[i] * 0.222f) + (blue[i] * 0.222f));
     r = componentCeiling(61.0f + grey);
     g = componentCeiling(87.0f + grey);
     b = componentCeiling(136.0f + grey);
     grey = (red[i] + green[i] + blue[i]) / 3;
     red[i] = truncate((int)(overlayPixelComponents(grey, r, 0.9f)));
     green[i] = truncate((int)(overlayPixelComponents(grey, g, 0.9f)));
     blue[i] = truncate((int)(overlayPixelComponents(grey, b, 0.9f)));
  }
}

      

Grain Filter

It is clear from the name that this filter adds grain to the image giving an artistic effect. It can be implemented in a very simple manner by assigning gray values to random pixels of an image. The condition inside the main for loop of the below implementation controls the proportion of added grain with respect to the whole image. For generating a random value, the timer has to be initialized first. The whole implementation of the function is shown below.

void applyGrain(Bitmap* bitmap) {
/*initializations*/
   time_t t;
   srand((unsigned) time(&t));
  for (i = length; i--;) {
       int rval = rand()%255;
       if (rand()%100 < 15)){
           int grey = (red[i] + green[i] + blue[i]) / 3;
           red[i] = truncate(rval);
           green[i] = truncate(rval);
           blue[i] = truncate(rval);
       }
  }
}

      

Threshold Filter

Thresholding an image gives a binary image i.e the pixels of the image will have only two values. One for a value less than the threshold and other for values greater than the threshold. The threshold value is adjusted by seek bar in Phimpme. An image looks very artistic for a particular value on the seek bar. Its implementation is shown below.

void applyThreshold(Bitmap* bitmap, int val) {
/*bitmap initializations*/
  unsigned char grey, color;
  int thres = 220 - (int)((val/100.0) * 190);
  for (i = length; i--;) {
       grey = (red[i] + green[i] + blue[i]) / 3;
       if (grey < thres) color = 0;
       else color = 255;
       red[i] = truncate((int)(color));
       green[i] = truncate((int)(color));
       blue[i] = truncate((int)(color));
  }
}

     

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