Object detection and image cropping using a multi-detector approach

A computer-implemented method of detecting objects within digital image data based at least in part on color transitions within the digital image data, the method comprising:

• receiving or capturing a digital image depicting an object;
• sampling color information from a first plurality of pixels of the digital image, wherein each of the first plurality of pixels is located in a background region of the digital image;
• optionally sampling color information from a second plurality of pixels of the digital image, wherein each of the second plurality of pixels is located in a foreground region of the digital image;
• generating or receiving a representative background color profile, the representative background color profile being based on the color information sampled from the first plurality of pixels;
• generating or receiving a representative foreground color profile based on the color information sampled from the second plurality of pixels and/or the color information sampled from the first plurality of pixels;
• assigning each pixel within the digital image a label of either foreground or background using an adaptive label learning process;
• binarizing the digital image based on the labels assigned to each pixel;
• detecting one or more contours within the binarized digital image;
• and
• defining one or more edges of the object based on the detected contour(s).

A computer program product for detecting objects within digital image data based at least in part on color transitions within the digital image data, the computer program product comprising a computer readable storage medium having embodied therewith computer readable program instructions configured to cause a processor, upon execution of the computer readable program instructions, to perform a method comprising:

• receiving or capturing a digital image depicting an object;
• sampling, using the processor, color information from a first plurality of pixels of the digital image, wherein each of the first plurality of pixels is located in a background region of the digital image;
• optionally sampling, using the processor, color information from a second plurality of pixels of the digital image, wherein each of the second plurality of pixels is located in a foreground region of the digital image;
• generating, using the processor, or receiving, by the processor, a representative background color profile, the representative background color profile being based on the color information sampled from the first plurality of pixels;
• generating, using the processor, or receiving, by the processor, a representative foreground color profile based on the color information sampled from the second plurality of pixels and/or the color information sampled from the first plurality of pixels;
• assigning, using the processor, each pixel within the digital image a label of either foreground or background using an adaptive label learning process;
• binarizing, using the processor, the digital image based on the labels assigned to each pixel;
• detecting, using the processor, one or more contours within the binarized digital image;
• and
• defining, using the processor, one or more edges of the object based on the detected contour(s).