System and method for detecting objects in an image
First Claim
1. A method for detecting, by a portable or a hand-held device, one or more rectangular-shaped object regions from a background in an image captured by a digital camera, the method by the device comprising:
- analyzing the captured image using a deep convolutional neural network for detecting the rectangular-shaped object regions;
cropping or extracting from the captured image each of the detected regions into a respective file; and
transmitting one or more of the files over a Wireless Local Area Network (WLAN) using a WLAN transmitter,wherein the neural network is further trained to recognize or classify the rectangular-shaped object regions in the captured image.
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Abstract
A method for cropping photos images captured by a user from an image of a page of a photo album is described. Corners in the page image are detected using corner detection algorithm or by detecting intersections of line-segments (and their extensions) in the image using edge, corner, or line detection techniques. Pairs of the detected corners are used to define all potential quads, which are then are qualified according to various criteria. A correlation matrix is generated for each potential pair of the qualified quads, and candidate quads are selected based on the Eigenvector of the correlation matrix. The content of the selected quads is checked using a salience map that may be based on a trained neuron network, and the resulting photos images are extracted as individual files for further handling or manipulation by the user.
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Citations
25 Claims
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1. A method for detecting, by a portable or a hand-held device, one or more rectangular-shaped object regions from a background in an image captured by a digital camera, the method by the device comprising:
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analyzing the captured image using a deep convolutional neural network for detecting the rectangular-shaped object regions; cropping or extracting from the captured image each of the detected regions into a respective file; and transmitting one or more of the files over a Wireless Local Area Network (WLAN) using a WLAN transmitter, wherein the neural network is further trained to recognize or classify the rectangular-shaped object regions in the captured image. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25)
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Specification