摘要:
An object classification method for a collision warning system is disclosed. The method includes the steps of capturing a video frame with an imaging device and examining a radar-cued potential object location within the video frame, extracting orthogonal moment features from the potential object location, extracting Gabor filtered features from the potential object location, and classifying the potential object location into one of a first type of image or a second type of image in view of the extracted orthogonal moment features and the Gabor filtered features.
摘要:
A stream of images including an area occupied by at least one object are processed to extract wavelet coefficients, and the extracted coefficients are represented as wavelet signatures that are less susceptible to misclassification due to noise and extraneous object features. Representing the wavelet coefficients as wavelet signatures involves sorting the coefficients by magnitude, setting a coefficient threshold based on the distribution of coefficient magnitudes, truncating coefficients whose magnitude is less than the threshold, and quantizing the remaining coefficients.
摘要:
A technique for identifying beam images of a beam matrix includes a number of steps. Initially, a plurality of light beams of a beam matrix, which are arranged in rows and columns, are received after reflection from a surface of a target. Next, a reference light beam is located in the beam matrix. Then, a row pivot beam is located in the beam matrix based on the reference beam. Next, remaining reference row beams of a reference row that includes the row pivot beam and the reference beam are located. Then, a column pivot beam in the beam matrix is located based on the reference beam. Next, remaining reference column beams of a reference column that includes the column pivot beam and the reference beam are located. Finally, remaining ones of the light beams in the beam matrix are located.
摘要:
A method of object detection includes receiving images of an area occupied by at least one object. Image features including wavelet features are extracted from the images. Classification is performed on the image features as a group in at least one common classification algorithm to produce object class confidence data.