Abstract: A motion detection method includes providing a buffer including a first buffer associated with a background image and a second buffer associated with a foreground image; checking first similarity between the gray level of an input pixel and the first gray level of the first buffer; determining the input pixel as a still pixel if the first similarity is true; checking second similarity between the gray level and the second gray level of the second buffer; determining the input pixel as a moving pixel if the second similarity is false; determining the input pixel as the moving pixel if the second count value is less than the first count value; and determining the input pixel as the still pixel and swapping the first buffer with the second buffer, if the second count value is not less than the first count value.

Abstract: A motion detection method includes providing a buffer including a first buffer associated with a background image and a second buffer associated with a foreground image; checking first similarity between the gray level of an input pixel and the first gray level of the first buffer; determining the input pixel as a still pixel if the first similarity is true; checking second similarity between the gray level and the second gray level of the second buffer; determining the input pixel as a moving pixel if the second similarity is false; determining the input pixel as the moving pixel if the second count value is less than the first count value; and determining the input pixel as the still pixel and swapping the first buffer with the second buffer, if the second count value is not less than the first count value.

Abstract: A method for compressing an image with bit rate control includes: compressing data of a current block with a compression level to produce compression data of the current block; in response to compression of the current block, accumulating a data size of compressed data of blocks that have been compressed to obtain an accumulated real size; in response to the compression of the current block, accumulating a target block size according to a number of blocks that have been compressed to obtain an accumulated target size; and adjusting the compression level for a next block according to at least the accumulated real size and the accumulated target size.

Abstract: A method of filtering a fingerprint image is provided. The method includes: receiving an input fingerprint image; preliminarily filtering the input fingerprint image to obtain a preprocessed image; normalizing and then filtering the preprocessed image to obtain a denoised image; filtering and then segmenting the preprocessed image to obtain a background mask; postprocessing the background mask to obtain a final mask; and applying the final mask to the denoised image to obtain an output fingerprint image.

Abstract: A method of filtering a fingerprint image is provided. The method includes: receiving an input fingerprint image; preliminarily filtering the input fingerprint image to obtain a preprocessed image; normalizing and then filtering the preprocessed image to obtain a denoised image; filtering and then segmenting the preprocessed image to obtain a background mask; postprocessing the background mask to obtain a final mask; and applying the final mask to the denoised image to obtain an output fingerprint image.

Abstract: An image processing method includes: receiving a raw input image; converting the raw input image into a binary input image; dividing the binary input image into N×M blocks; determining whether a specific block is a moving block; determining whether the specific block is a connected image component which is connected to at least one corresponding neighboring block when the specific block is determined as the moving block; and, determining a bounding box according to a result of whether the specific block is the connected image component connected to at least one corresponding neighboring block.

Abstract: A method for compressing an image with bit rate control includes: compressing data of a current block with a compression level to produce compression data of the current block; in response to compression of the current block, accumulating a data size of compressed data of blocks that have been compressed to obtain an accumulated real size; in response to the compression of the current block, accumulating a target block size according to a number of blocks that have been compressed to obtain an accumulated target size; and adjusting the compression level for a next block according to at least the accumulated real size and the accumulated target size.

Abstract: Disclosed is a fingerprint identification system comprising an image acquiring device and a processing circuit. The image acquiring device acquires at least one second image. The processing circuit performs following steps: (a) selecting a plurality of first align points from first ridge points of a first image, and selecting a plurality of second align points from second ridge points of the second image; (b) pairing at least one of the second align points to at least one first paired align point among the first align points; (c) calculating at least one transform function based on the second align point and the first paired align point; and (d) transforming the second image to a second transformed image according to the transform function, and determining if the second image matches any part of the first image according to the second transformed image and at least part of the first image.

Abstract: The method includes: setting up a hierarchy structure, wherein the hierarchy structure includes more than 2 levels, each slice in a lowest level of the levels is a single fingerprint image generated by a fingerprint sensor, a slice in a second level of the levels includes at most M slices in a first level of the levels, the second level is one level higher than the first level, and M is a positive integer greater than 1; obtaining a new fingerprint image, adding the new fingerprint image into the lowest level, arid updating the hierarchy structure; and outputting an enroll fingerprint image according to a slice in a highest level.

Abstract: The method includes: setting up a hierarchy structure, wherein the hierarchy structure includes more than 2 levels, each slice in a lowest level of the levels is a single fingerprint image generated by a fingerprint sensor, a slice in a second level of the levels includes at most M slices in a first level of the levels, the second level is one level higher than the first level, and M is a positive integer greater than 1; obtaining a new fingerprint image, adding the new fingerprint image into the lowest level, arid updating the hierarchy structure; and outputting an enroll fingerprint image according to a slice in a highest level.

Abstract: The present invention is directed to a rate-distortion optimized (RDO) transform and quantization system. A frame classification unit classifies an input frame as either a key frame or a non-key frame. A rate model update unit generates at least one model parameter of a rate model according to a transform coefficient and a bitrate resulted from an encoded key frame. An RDO transform and quantization unit processes the input frame, thereby generating a quantized transform coefficient according to the model parameter. A frame buffer is used to store a previous frame, according to which the bitrate is estimated.

Abstract: A rate-distortion optimized quantization method includes determining a rate model and a distortion model respectively, establishing a rate-distortion objective function according to the rate model and the distortion model, estimating a closed-form solution for the rate-distortion objective function, and according to an input frame generating quantized transform coefficients using the closed-form solution.

Abstract: The present invention is directed to a rate-distortion optimized (RDO) transform and quantization system. A frame classification unit classifies an input frame as either a key frame or a non-key frame. A rate model update unit generates at least one model parameter of a rate model according to a transform coefficient and a bitrate resulted from an encoded key frame. An RDO transform and quantization unit processes the input frame, thereby generating a quantized transform coefficient according to the model parameter. A frame buffer is used to store a previous frame, according to which the bitrate is estimated.