How to detect and highlight the edges of an image in Java

Edge detection can be a difficult feature to implement into a photo app. Today, we will be looking at how to accomplish this without all the headache. In fact, we should be finished in just a few minutes. Let’s get started

First we need to dynamically compile our library using Jitpack. This will require the following references to be added to pom.xml:

Repository

<repositories>
    <repository>
        <id>jitpack.io</id>
        <url>https://jitpack.io</url>
    </repository>
</repositories>

Dependency

<dependencies>
<dependency>
    <groupId>com.github.Cloudmersive</groupId>
    <artifactId>Cloudmersive.APIClient.Java</artifactId>
    <version>v2.75</version>
</dependency>
</dependencies>

Now call filterEdgeDetect, provide an image and effect radius:

// Import classes:
//import com.cloudmersive.client.invoker.ApiClient;
//import com.cloudmersive.client.invoker.ApiException;
//import com.cloudmersive.client.invoker.Configuration;
//import com.cloudmersive.client.invoker.auth.*;
//import com.cloudmersive.client.FilterApi;
ApiClient defaultClient = Configuration.getDefaultApiClient();
// Configure API key authorization: Apikey
ApiKeyAuth Apikey = (ApiKeyAuth) defaultClient.getAuthentication("Apikey");
Apikey.setApiKey("YOUR API KEY");
// Uncomment the following line to set a prefix for the API key, e.g. "Token" (defaults to null)
//Apikey.setApiKeyPrefix("Token");
FilterApi apiInstance = new FilterApi();
Integer radius = 56; // Integer | Radius in pixels of the edge detection operation; a larger radius will produce a greater effect
File imageFile = new File("/path/to/file"); // File | Image file to perform the operation on.  Common file formats such as PNG, JPEG are supported.
try {
byte[] result = apiInstance.filterEdgeDetect(radius, imageFile);
System.out.println(result);
} catch (ApiException e) {
System.err.println("Exception when calling FilterApi#filterEdgeDetect");
e.printStackTrace();
}

And we are done! It’s really that simple. Let’s use this photo to test it out:

We shall set the radius to 1 and here is what we get: