Content-based image object retrieval by scale-space representation of shapes

Vast amounts of inexpensive storage and cost-effective input devices have promoted a rapid increase in the amount of stored digital images and video. Retrieving desired images from image databases is a challenging problem, not easily solved by existing database methods. Shape is one popular feature used to automate retrieval of images by content. Example shape features include the Fourier descriptor for describing shape boundaries, and area or compactness for describing shape regions, among others. We present a new shape-representation method based on extracting an image surface ridge-line called the Most Prominent Ridge-Line (MPRL) in scale-space. The MPRL is extracted by minimizing the second spatial derivative orthogonal to the ridge-line direction. The scale of the MPRL point is proportional to the image object's width. Matching query and database image MPRLs is shown to be an effective method for retrieving images based on shape. A unique feature of the proposed method is that the scale dimension may be weighted to allow for any desired amount of shape details in image retrieval.