This paper proposes a fast algorithm for rotating images while preserving their quality. The new approach rotates images based on vertical or horizontal lines in the original image and their rotated equation in the target image. The proposed method is a one-pass method that determines a based-line equation in the target image and extracts all corresponding pixels on the base-line. Floating-point multiplications are performed to calculate the base-line in the target image, and other line coordinates are calculated using integer addition or subtraction and logical justifications from the base-line pixel coordinates in the target image. To avoid a heterogeneous distance between rotated pixels in the target image, each line rotates to two adjacent lines. The proposed method yields good performance in terms of speed and quality according to the results of an analysis of the computation speed and accuracy.

In this paper, an Iranian vehicle license plate recognition system based on a new localization approach, which is modified to reflect the local context, is proposed, along with a hybrid classifier that recognizes license plate characters. The method presented here is based on a modified template-matching technique by the analysis of target color pixels to detect the location of a vehicle’s license plate. A modified strip search enables localization of the standard color-geometric template utilized in Iran and several European countries. This approach uses periodic strip search to find the hue of each pixel on demand. In addition, when a group of target pixels is detected, it is analyzed to verify that its shape and aspect ratio match those of the standard license plate. In addition to being scale and rotation invariant, this method avoids time-consuming image algorithms and transformations for the whole image pixels, such as resizing and Hough, Fourier, and wavelet transforms, thereby cutting down the detection response time. License plate characters are recognized by a hybrid classifier that comprises a decision tree and a support vector machine with a homogeneous fifth-degree polynomial kernel. The performance detection rate and the overall system performance achieved are 96% and 94%, respectively.