141 results about "JPEG" patented technology

The invention relates to the technical field of information encryption and decryption, in particular to an image information encryption and decryption method and software system based on a digital image steganography technology. According to the technical scheme, the method comprises the following steps that a carrier image format and a to-be-processed information type are determined, the carrier image format comprises a PNG image and a JPEG image, and the to-be-processed information type comprises text information, picture information and audio information; encrypting the plaintext information to generate ciphertext information; and selecting a corresponding steganography path according to the format of the carrier image, embedding the ciphertext information into the carrier image, generating an encrypted image, and generating a key file recording the embedded related information. According to the method, various image formats and information types are supported, the compatibility, safety, robustness and practicability of information encryption and decryption are improved through key encryption, face binding verification and a compensation mechanism for JPEG, and the method is suitable for scenes such as information protection and private transmission.

The invention discloses a railway driver driving behavior monitoring method based on artificial intelligence. An artificial intelligence processing unit completes hardware interface initialization; the integrated wireless equipment of the railway locomotive sends a network IP address and equipment identification information of the main control end to a host process of the artificial intelligence processing unit; a host process of the artificial intelligence processing unit initiates a video stream pulling request to a digital camera at a corresponding end through an RTSP protocol; the main process of the artificial intelligence processing unit receives the RTSP code stream and then decodes the RTSP code stream into a picture in a JPEG format, the image is cut and zoomed, and complete metadata information is added for each picture; three reasoning processes of the artificial intelligence processing unit run in parallel, and each process performs targeted reasoning detection on the decoded JPEG picture and metadata based on a self-loaded model: a main process receives a reasoning detection result, performs comprehensive judgment in combination with a preset threshold value and an abnormal state duration, and sends the result to the main process; triple alarms of local reminding, driver informing and remote monitoring are realized, and the driving behavior of the driver is standardized.

A kind of railway driver driving behavior monitoring method based on artificial intelligence, artificial intelligence processing unit completes hardware interface initialization;Railway locomotive comprehensive wireless device sends the network IP address of main control end, device identification information to the main process of artificial intelligence processing unit;Artificial intelligence processing unit main process initiates video stream pull request to the digital camera of corresponding end by RTSP protocol;Artificial intelligence processing unit main process decodes into JPEG format picture after receiving RTSP code stream, trims zoom image, adds complete metadata information to each picture;Three inference processes of artificial intelligence processing unit run in parallel, each process is based on the model loaded by itself to decode the JPEG picture and metadata for targeted inference detection:Main process receives inference detection result, carries out comprehensive judgment in conjunction with preset threshold and abnormal state duration, realizes local reminder, driver notification, remote monitoring triple alarm, standardizes driver driving behavior.

The application provides a JPEG data decoding method and device, equipment and storage medium, which can be used in the field of image processing. The method comprises the following steps: obtaining target JPEG data, marking the target JPEG data based on a preset segmentation length in units of target MCUs to obtain target JPEG segmented data; storing the target JPEG segmented data into a target SVM to obtain multiple initial decoded segments and synchronization parameter information; in response to the multiple initial decoded segments being correctly decoded, judging whether the number of target MCUs corresponding to the multiple initial decoded segments meets a preset number condition; if yes, sending a target decoding instruction to a target GPU to enable the target GPU to perform target Huffman decoding to obtain multiple target decoded segments; decoding each target DCU included in each target decoded segment to obtain target JPEG decoding data; and storing the target JPEG decoding data into the target SVM to obtain a target RGB image corresponding to the target JPEG decoding data based on the target GPU. The CPU running load is reduced, and the decoding efficiency is improved.

The invention discloses an image compression method based on a JPEG-LS (Joint Photographic Experts Group-Least Squares) parallel optimization algorithm, which comprises the following steps: calculating local gradient values of to-be-coded data and then merging to obtain a context index Q value, the to-be-coded data being a prediction error of a current pixel; grouping the data to be coded according to the context index Q value; if the to-be-coded number contained in the key group affects the parallelism degree, a controllable distortion value is introduced into the pixel value of the to-be-coded data by using an equalization algorithm, and the group serial number corresponding to the data in the key group is corrected; deploying processing units of parallel channels with the number equal to that of the groups, and scheduling the grouped data to be coded to the processing units to realize pipeline processing; integrating each group of data into coded and compressed data through code stream splicing; the image compression method based on the JPEG-LS parallel optimization algorithm is used for image compression, the system data size is low, and the satellite-ground transmission bandwidth pressure is small.

The invention relates to the field of sign language translation. The invention discloses a sign language real-time translation system based on multi-dimensional data fusion. The sign language real-time translation system comprises an image information acquisition module, a data processing module and a result display module, the image information acquisition module captures sign language actions of a user in real time through a camera to generate sign language videos, and operates four core task architectures including an HTTP server task, a camera acquisition task, a streaming media transmission task and a video downloading task on the basis of FreeRTOS, the HTTP server task receives a client request, and the video downloading task receives the client request. Comprising an MJPEG video stream, a JPEG single frame capture and a video downloading access endpoint, a built-in CORS cross-domain access support, a camera acquisition task continuously captures JPEG frames with a fixed frame rate, each task is connected with a queue transfer client through semaphore protection frame data to realize efficient collaboration, multi-task parallel processing is realized, the transmission frame rate is accurately controlled to meet the algorithm requirement, and the algorithm requirement is met. And ESP32 dual-core resources are utilized to the maximum extent.

An image steganography analysis method based on a hybrid deep learning framework combines the feature extraction advantage of a JPEG steganography rich model and the integratable advantage of a deep learning model to construct a multi-stage hybrid deep learning JPEG steganography analysis framework, and the framework has expandability and can be applied to image steganography analysis. The latest deep learning steganalysis network can be added to the framework. Meanwhile, the steganalysis problem under various complex scenes such as data source mismatching can also be adapted; a color image steganalysis CNN trunk model formed by three stages of preprocessing, feature extraction and feature classification is designed, and a space attention mechanism and a channel attention mechanism are added in a trunk stream, so that the detection accuracy is improved; a new algorithm optimization module is designed based on the framework, the network structure is adjusted, and the generalization ability, convergence performance, detection accuracy and robustness of the model are further improved.

The invention provides a residual DCT (Discrete Cosine Transformation) feature guided artifact learning module and an image tampering detection system, and the module comprises a DCT coefficient processing unit, a quantization table processing unit, a residual DCT calculation unit, a feature splicing unit and a neural convolution processing unit. The residual DCT calculation unit is used for performing repeated recompression on DCT coefficient matrix simulation JPEG compression to obtain DCT residual information and construct a residual DCT feature map on the basis of the DCT residual information, and the DCT coefficient processing unit is used for encoding the DCT coefficient matrix into DCT plane binary volume representation by using threshold truncation and One-Hot encoding, and then performing feature extraction and processing; the quantization table processing unit is used for expanding and processing a quantization table; the feature splicing unit is used for feature splicing; and the neural convolution processing unit is used for processing the spliced features to obtain final DCT features. According to the method, the positioning and identification capability of the tampered area in the double JPEG image with the same QF compressed twice is effectively improved.

A diffusion model is augmented with pseudoinverse guidance to restore data, removing artifacts and generating high-quality reconstructed data from limited, low-quality and / or noisy input data. The low-quality input data is denoised by a diffusion model and the denoised input data is combined with a guidance term to produce output data of higher-quality compared with the low-quality input data. The guidance term is a vector-Jacobian product that encourages consistency between the denoised input data and measurements after a pseudoinverse transformation. The denoising process may be applied in an iterative fashion to generate valid solutions to the inverse problem. The augmented diffusion model is a problem-agnostic (e.g., plug-and-play) denoiser that can restore data for a variety of tasks. Example image restoration tasks include denoising, JPEG denoising, deblurring, outpainting, inpainting, colorization, high-dynamic range, and super-resolution.

A system and method for energy-efficient approximate digital JPEG and MJPEG-compression. The system includes a controller unit to control a processing loop for processing image blocks based on a comparison of a current image block to a previous image block. The system includes a quantization unit configured to quantize the frequency domain representation using an approximate quantization process and a quantization (Q) matrix. The quantization unit is configured to: identify, a nearest power of two value for each element of the quantization matrix; generate an updated Q matrix by assigning each element of the quantization matrix with the identified nearest power of two value; and shift each element of the updated Q matrix by a number of bits to generate a quantized frequency domain representation. The number of bits corresponds to the identified nearest power of two for the corresponding element of the updated Q matrix.

The application provides a method for detecting synchronous JPEG recompression of BMP format concealed images, and a method for effectively estimating a JPEG quantization table is provided; by using the particularity of JPEG 100 quality factor compression, the minimum error caused by JPEG compression when the quality factor is 100 is extracted to construct an expected-minimum error feature; by using the convergence characteristics of inverse quantization JPEG coefficients, a first-order relative error feature is proposed, and finally synchronous JPEG recompression images saved in BMP format are effectively detected, and synchronous JPEG recompression at any quality factor can also be detected. The application can effectively distinguish single compressed images from recompressed images, and has higher accuracy compared with corresponding traditional JPEG recompression detection methods.

The invention discloses a JPEG image batch steganography method and system based on experience security, and belongs to the technical field of information security. The method comprises the following steps: screening batch steganography carriers from a candidate JPEG image set based on experience security; calculating a non-zero DCT coefficient feature and a cost response curve D-alpha of each batch of steganography carriers; and calculating the optimal load rate of each batch of steganography carriers based on the non-zero DCT coefficient characteristics, the cost response curve D-alpha and the length of the load message, and executing steganography of the load message according to the optimal load rate. According to the method, the security of large-batch image steganography communication under an adaptive steganography algorithm can be improved.

The invention relates to a non-standard JPEG (Joint Photographic Experts Group) coding processing method for dynamic code rate control. The method comprises the following steps: presetting a multi-frame joint image processing scene, obtaining an original reference image, and carrying out combined processing of boundary expansion and random bias addition to obtain a preprocessed reference image; dividing macro blocks for the preprocessed reference image, and distributing an independent coding parameter configuration space after verification and compliance; frequency domain conversion is executed according to a division result, an initial quantization parameter is calculated through an index model, and a dynamic quantization table is dynamically adjusted; executing non-standard entropy coding to obtain an indexed macro block coding code stream; combining the indexed code stream and a macro block division result to construct an index table containing a macro block serial number, an initial address and a code stream length; analyzing the code stream to obtain quantized data, and performing inverse quantization by using a dynamic quantization table to obtain spatial domain data; enabling the format of the reconstructed image to be consistent with that of the preprocessed reference image through reverse preprocessing, and performing real-time processing on the linkage input image to obtain a reconstructed reference image; and non-standard JPEG coding processing of dynamic code rate control is realized.

This article 11 is a fixture for detachably attaching a first article and a second article. As shown in Reference FIG. 1 and Reference FIG. 2 (a cross-sectional view taken along CC in Reference FIG. 1), this article 11 includes a plate- or sheet-like base portion 21, an engagement portion 31 attached (e.g., by adhesive, sticking, or fusion) to one surface 22 of the two main surfaces 22, 23 of the base portion 21, and an attraction portion 41 (here, a permanent magnet) embedded in the base portion 21 in an annular shape (along a circle on the one surface 22, centered on a central axis K, which will be described later). The engagement portion 31 includes a disk-shaped engagement main body portion 33 (both main surfaces of which are plate-shaped and form a circle centered on the central axis K) and three claw portions 35a, 35b, and 35c formed to protrude from the outer periphery of the engagement main body portion 33. This article 11 can be detachably engaged with a receiver. As shown in Reference Figure 3 and Reference Figure 4 (viewed from the opposite direction to Reference Figure 3), an example receiver 71 is formed of an annular member. Reference Figure 5 is a cross-sectional view of Reference Figure 3 taken along line AA, and Reference Figure 6 is an enlarged view of circle F in Reference Figure 5. Reference Figure 7 is a cross-sectional view of Reference Figure 3 taken along line BB, Reference Figure 8A is an enlarged view of circle G in Reference Figure 7, and Reference Figure 8B is an enlarged view of circle H in Reference Figure 7. As shown in Reference Figure 9 showing the structure (which shows the receiver 71 viewed from the same direction as Reference Figure 4 showing the structure), the receiver 71 has a first inner surface 75 (forming the side of a right circular cylinder (radius r1) with a central axis J perpendicular to Reference Figure 9 showing the structure) formed on the bottom surface 73 side, and a second inner surface 77 (forming the side of a right circular cylinder (radius r2) with a central axis J as its axis) formed on the surface 74 (the surface that appears in Reference Figure 3 showing the structure) side opposite the bottom surface 73 (the surface that appears in Reference Figure 3 showing the structure). The parts other than those painted in black are the parts for which design registration is sought. This design is represented by a drawing substitute sample or model, so please refer to the original for details and colors.View showing front, top and right side of sample JPEG 0001812574000001.jpg 113 150 View showing back, bottom and left side of sample JPEG 0001812574000002.jpg 113 150 Front view of sample JPEG 0001812574000003.jpg 113 150 Back view of sample JPEG 0001812574000004.jpg 113 150 Right side view of sample JPEG 0001812574000005.jpg 113 150 Left side view of sample JPEG 0001812574000006.jpg 113 150 Top view of sample JPEG 0001812574000007.jpg 113 150 Bottom view of sample JPEG 0001812574000008.jpg 113 150 Reference diagram 1 showing structure JPEG 0001812574000009.jpg 53 56 Reference diagram 2 showing structure JPEG 0001812574000010.jpg 34 64 Reference diagram 3 showing structure JPEG 0001812574000011.jpg 41 43 Reference diagram 4 showing structure JPEG 0001812574000012.jpg 31 41 Reference diagram 5 showing structure JPEG 0001812574000013.jpg 40 24 Reference diagram 6 showing structure JPEG 0001812574000014.jpg 34 21 Reference diagram 7 showing the structure JPEG 0001812574000015.jpg 23 43 Reference diagram 8A showing the structure JPEG 0001812574000016.jpg 16 38 Reference diagram 8B showing the structure JPEG 0001812574000017.jpg 20 37 Reference diagram 9 showing the structure JPEG 0001812574000018.jpg 46 49 Reference diagram 1 showing the usage state JPEG 0001812574000019.jpg 73 76 Reference diagram 2 showing the usage state JPEG 0001812574000020.jpg 30 64 Reference diagram 3 showing the usage state JPEG 0001812574000021.jpg 74 83 Reference diagram 4 showing usage status JPEG 0001812574000022.jpg 32 64.

This article 11 is a fixture for detachably attaching a first article and a second article. As shown in Reference FIG. 1 and Reference FIG. 2 (a cross-sectional view taken along CC in Reference FIG. 1), this article 11 includes a plate- or sheet-like base portion 21, an engagement portion 31 attached (e.g., by adhesive, sticking, or fusion) to one surface 22 of the two main surfaces 22, 23 of the base portion 21, and an attraction portion 41 (here, a permanent magnet) embedded in the base portion 21 in an annular shape (along a circle on the one surface 22, centered on a central axis K, which will be described later). The engagement portion 31 includes a disk-shaped engagement main body portion 33 (both main surfaces of which are plate-shaped and form a circle centered on the central axis K) and three claw portions 35a, 35b, and 35c formed to protrude from the outer periphery of the engagement main body portion 33. This article 11 can be detachably engaged with a receiver. As shown in Reference Figure 3 and Reference Figure 4 (viewed from the opposite direction to Reference Figure 3), an example receiver 71 is formed of an annular member. Reference Figure 5 is a cross-sectional view of Reference Figure 3 taken along line AA, and Reference Figure 6 is an enlarged view of circle F in Reference Figure 5. Reference Figure 7 is a cross-sectional view of Reference Figure 3 taken along line BB, Reference Figure 8A is an enlarged view of circle G in Reference Figure 7, and Reference Figure 8B is an enlarged view of circle H in Reference Figure 7. As shown in Reference Figure 9 showing the structure (which shows the receiver 71 viewed from the same direction as Reference Figure 4 showing the structure), the receiver 71 has a first inner surface 75 (forming the side of a right circular cylinder (radius r1) with a central axis J perpendicular to Reference Figure 9 showing the structure) formed on the bottom surface 73 side, and a second inner surface 77 (forming the side of a right circular cylinder (radius r2) with a central axis J as its axis) formed on the surface 74 (the surface that appears in Reference Figure 3 showing the structure) side opposite the bottom surface 73.This design is represented by a drawing substitute sample or template, so please refer to the original for details and colors.View showing front, top and right side of sample JPEG 0001812573000001.jpg 113 150 View showing back, bottom and left side of sample JPEG 0001812573000002.jpg 113 150 Front view of sample JPEG 0001812573000003.jpg 113 150 Back view of sample JPEG 0001812573000004.jpg 113 150 Right side view of sample JPEG 0001812573000005.jpg 113 150 Left side view of sample JPEG 0001812573000006.jpg 113 150 Top view of sample JPEG 0001812573000007.jpg 113 150 Bottom view of sample JPEG 0001812573000008.jpg 113 150 Reference diagram 1 showing structure JPEG 0001812573000009.jpg 53 56 Reference diagram 2 showing structure JPEG 0001812573000010.jpg 34 64 Reference diagram 3 showing structure JPEG 0001812573000011.jpg 41 43 Reference diagram 4 showing structure JPEG 0001812573000012.jpg 31 41 Reference diagram 5 showing structure JPEG 0001812573000013.jpg 40 24 Reference diagram 6 showing structure JPEG 0001812573000014.jpg 34 21 Reference diagram 7 showing the structure JPEG 0001812573000015.jpg 23 43 Reference diagram 8A showing the structure JPEG 0001812573000016.jpg 16 38 Reference diagram 8B showing the structure JPEG 0001812573000017.jpg 20 37 Reference diagram 9 showing the structure JPEG 0001812573000018.jpg 46 49 Reference diagram 1 showing the usage state JPEG 0001812573000019.jpg 73 76 Reference diagram 2 showing the usage state JPEG 0001812573000020.jpg 30 64 Reference diagram 3 showing the usage state JPEG 0001812573000021.jpg 74 83 Reference diagram 4 showing usage status JPEG 0001812573000022.jpg 32 64.

A system and method for energy-efficient approximate digital JPEG and MJPEG-compression. The system includes a controller unit to control a processing loop for processing image blocks based on a comparison of a current image block to a previous image block. The system includes a quantization unit configured to quantize the frequency domain representation using an approximate quantization process and a quantization (Q) matrix. The quantization unit is configured to: identify, a nearest power of two value for each element of the quantization matrix; generate an updated Q matrix by assigning each element of the quantization matrix with the identified nearest power of two value; and shift each element of the updated Q matrix by a number of bits to generate a quantized frequency domain representation. The number of bits corresponds to the identified nearest power of two for the corresponding element of the updated Q matrix.

The application discloses a method for urine test paper mobile phone image detection and analysis, which comprises the following steps: collecting urine test paper JPEG images under multiple light sources under a standard light source box, taking the test paper image under the D65 light source as a standard image, converging the RGB color performance of the test paper block in the corresponding area of the test paper image under the standard light source to the test paper image under the remaining light source environment, that is, training and obtaining a compensation model, fully considering the test paper color features and the mobile phone camera characteristic features in the model characteristic parameters, ensuring the accuracy of the color correction model by analyzing the maximum value, minimum value and variance of the features during preprocessing, establishing a training TabNet model, fusing multiple regression models such as LightGBM, ElasticNet Regression and Support Vector Regression to optimize the color correction effect, and realizing a strengthened compensation model. Through the color correction of the test paper image by the compensation model, the error caused by the color performance of the urine test paper image affected by the environmental light is reduced, the most real color of the test paper image is restored, the color recognition degree is improved, the accuracy of the test paper detection and analysis is improved, and the model is small and has a fast recognition speed.

The present application belongs to the field of image processing and target detection, and specifically provides a RAW image processing method for target detection, which is used to improve the compression efficiency of the image, and can significantly improve the recognition accuracy when the processed image is applied to the target detection task. The present application constructs a semantic fusion network to directly generate an image from the RAW image, which is more suitable for detection and occupies less storage. In the present application, the RAW image retains a large amount of original information, and the semantic information is obtained through the JPEG image and the label provided thereby, which is integrated into the RAW image processed by the ISP. While taking into account the detection accuracy, the required number of bits for image transmission is effectively reduced. At the same time, an efficient and close-to-training-target loss function is used to constrain the entire training process, which can significantly reduce the space occupied by the image and improve the detection rate. In summary, after introducing the RAW image processing method for target detection, the present application can improve the recognition accuracy and reduce the demand for storage space.

The invention provides a real-time three-dimensional reconstruction method and system based on unmanned equipment. In order to solve the lag problem that in traditional reconstruction, collection needs to be conducted firstly and then reconstruction needs to be conducted, and the composite bottleneck that airborne computing power is limited and weak network bandwidth is insufficient, a unified time signal is generated through a hardware synchronization module, and microsecond-level synchronization of multi-source data is achieved; aiming at heterogeneous data characteristics, the airborne end respectively constructs batch processing assembly lines of point cloud octree compression, image JPEG coding and IMU byte alignment, so that the data volume is remarkably compressed while the computing power overhead is reduced; a QoS mechanism and local persistent cache of an MQTT protocol are introduced into a transmission layer, and reliable arrival of data during network fluctuation is guaranteed through a breakpoint resume technology. In conclusion, end-to-end real-time processing of software and hardware collaboration is realized, bandwidth occupation is effectively reduced, and stable and high-precision real-time three-dimensional reconstruction is realized in a weak network environment.

The application relates to a kind of implementation methods of FPGA-based JPEG-LS encoder, sequentially including context modeling, edge detection, adaptive prediction correction, prediction residual calculation, Golomb coding parameter K calculation, prediction error mapping, Golomb coding is carried out to prediction error MErrval, context parameter update and code stream splicing.This application can realize JPEG-LS lossless high compression rate encoder function on the basis of hardware without the aid of software.One aspect, discard the run length coding in JPEG-LS standard, reduce the complexity of hardware implementation, reduce the consumption of the hardware resource of the designed encoder, the application also obtains the encoder with compression rate of 18%~25% by optimizing the calculation of golomb coding parameter K and golomb coding mode.

The invention provides an infrared image watermark adding method and system, and the method comprises the following steps: obtaining an original infrared image, and carrying out the analysis of the original infrared image, so as to obtain the infrared radiation intensity of the original infrared image; generating a watermarking-free base map according to the infrared radiation intensity; moving the watermarking-free base map to an image display area, and performing zooming processing on the watermarking-free base map in the image display area, so that the watermarking-free base map and the image display area are consistent in size; and drawing a watermark on the watermark-free base map in the image display area to generate an infrared image with the watermark. According to the method, a JPEG or JPG image is not directly used as a watermark to draw a background image, the YUV image is zoomed, and the watermark is finally added, so that the definition of the watermark can be ensured, the infrared image after the watermark is drawn can still have high resolution, and the problem that the watermark drawing display on the infrared low-resolution image is blurred is solved.

The application discloses a JPEG image multi-carrier steganography method based on a monkey king evolution algorithm, which is used for embedding secret information into images and comprises the following steps: processing N images according to a user input password and an error correction matrix H based on a (7, 4) Hamming code to obtain N carrier images, wherein a matrix of the i-th carrier image is H i ′, i = 1, 2,..., N; converting secret information to be embedded Secret into a binary form, and encrypting to obtain a binary sequence M = (m1, m2,..., m L L is the length of the binary sequence M; taking the minimum difference between a carrier image feature set and a stego image feature set as an objective, using a monkey king evolution algorithm to perform non-uniform dynamic allocation on the load size of each carrier image, and according to the allocation result, cutting and writing the secret information into the corresponding carrier image to obtain a stego image set. The application can solve the problem of efficient allocation of secret information among multiple carrier images, so that the stego image is least detected.

This invention discloses a satellite image compression method under extremely low bandwidth conditions. The steps are as follows: collect a static image dataset; establish a variable bitrate image encoding / decoding network; train the encoding / decoding network; embed a generative adversarial network (GAN) at the decoder and retrain it; embed a super-resolution network after the encoder / decoder and retrain it; the user selects a region of interest (ROI), and the selected region is compressed; the decoder restores the bitstream to an image and displays it; the unselected regions are compressed; when bandwidth is sufficient, the unselected regions are transmitted, and the decoder stitches the images together; super-resolution processing is performed. This image transmission method, under extremely low bandwidth constraints, provides a superior subjective reconstruction effect compared to traditional image coding methods such as JPEG and deep learning-based image coding methods in a large number of test images.

The application discloses a lossy compression detection method and terminal fusing high-frequency space domain and DCT domain, and the method comprises the steps of obtaining a first JPEG compressed image data set, training a WebP lossy compression detection network according to the first JPEG compressed image data set to obtain a trained WebP lossy compression detection network, obtaining a second JPEG compressed image data set, performing WebP lossy compression trace detection on the second JPEG compressed image data set according to the trained WebP lossy compression detection network, and outputting a detection result; the method for extracting features of a JPEG image by fusing high-frequency space domain and DCT domain provided by the application solves the problem that the effect of the lossy compression detection method for JPEG double compression in the prior art is poor and even fails in some cases.

A mechanism for processing video data is disclosed. The mechanism includes determining to signal dynamic metadata rendering information in a Joint Photographic Experts Group (JPEG) Artificial Intelligence (AI) codestream, wherein the dynamic metadata rendering information is signalled in a syntax structure comprising, an indication of a dynamic metadata type, an indication of a size of a dynamic metadata, and data bytes of the dynamic metadata. A conversion is performed between a visual media data and the JPEG AI codestream based on the dynamic metadata rendering information.

The embodiment of the invention discloses a bill analysis method and system. The method comprises the following steps: receiving an external request; analyzing a head feature code of the bill data, if a JPEG or PNG file identifier is detected, routing the bill data to an image processing channel, calling an OCR engine to perform full-graph identification on the bill data, and based on a province template corresponding to the provincial administrative region code, extracting a preset field from the bill data as an analysis result; if the PDF identifier is identified, routing the bill data to a PDF processing channel, and executing text layer extraction and seal detection on the bill data in parallel to obtain an analysis result; and according to the province template, mapping an analysis result into a standard JSON structure, performing field integrity, logic rationality and cross-field relevance verification on the standard JSON structure, and outputting the standard JSON structure after the verification is passed. According to the embodiment of the invention, the recognition precision of the bill data can be remarkably improved, the processing efficiency of bill analysis is comprehensively optimized, and the resource utilization efficiency is improved.

The invention belongs to the technical field of data processing, and discloses a color JPEG reversible watermark hiding method and system based on adaptive STC, and the method comprises the steps: obtaining a color JPEG image, decoding the color JPEG image, converting the color JPEG image into a Y color space, and extracting the DCT coefficients of the Y channel and the Y channel; according to the statistical characteristics of the DCT coefficients of all the channels, the embedding adaptability weight is calculated, and the embedding capacity is adaptively allocated to the three channels in combination with a preset channel weighting adjustment factor; a candidate set is selected according to the sequence of the three channels and the distributed embedding capacity, and zero value coefficients in the candidate set form a carrier sequence; the watermark to be hidden is embedded into the carrier sequence through STC coding, the secret-carrying JPEG image is generated, and high-capacity, low-distortion and completely reversible watermark hiding facing the color JPEG image is achieved.

The invention discloses a high-throughput JPEG (Joint Photographic Experts Group) heterogeneous reasoning and hybrid parallel method on mobile equipment, and provides an FCG reasoning framework aiming at the problems of high decoding time consumption proportion, high cross-processor communication overhead and low processor resource utilization rate in the existing mobile terminal JPEG image recognition. And optimization is carried out by combining JPEG frequency domain information with characteristics of a heterogeneous processor of a mobile terminal. The framework comprises an off-line preprocessing stage, an off-line task division stage and an on-line task scheduling stage, wherein in the off-line preprocessing stage, processor operation data are collected, and a delay prediction model is established; in the off-line task division stage, a processor cluster is constructed, model tasks are distributed, and the task amount is adjusted; and in the online task scheduling stage, hybrid parallel pipeline identification is executed according to the scheme. According to the method, through multi-core Huffman decoding, heterogeneous network structure design and optimization of task scheduling, the identification delay is remarkably reduced, the throughput is improved, the energy consumption is reduced, and the batch JPEG image identification performance of the mobile terminal is effectively improved.

The present application relates to the technical field of image processing, and particularly relates to an image processing method, an electronic device and a readable storage medium, the image processing method comprises the following steps: fusing and blocking a current frame and a reference frame to obtain a plurality of to-be-encoded spatial image blocks, and combining the to-be-encoded spatial image blocks into a plurality of macroblocks, and configuring a corresponding encoding quantization table and a decoding quantization table for each macroblock; performing discrete cosine transform by using a first integer DCT transform kernel; performing quantization by using the encoding quantization table; performing entropy encoding and storing into an off-chip memory; reading a compressed code stream from the off-chip memory, performing entropy decoding, and performing inverse quantization by using the decoding quantization table; performing inverse discrete cosine transform by using a second integer DCT transform kernel; performing block recombination to obtain a reconstructed reference frame, and taking the reconstructed reference frame as a new reference frame, taking a next frame input as a new current frame, and recycling. The present application can effectively solve the technical problem of distortion accumulation in the multi-round iteration encoding and decoding process based on JPEG.

Various systems and methods are presented regarding generating executable computer code / instructions from input files, whereby the input files may be an image file (e.g., JPEG, PDF, etc.). The image file can be digital capture of a sequence of instructions such as a graphical representation comprising a ladder diagram, a function block diagram, a sequential function chart, etc. P&ID and suchlike can also be submitted to the system. Code generated from the input files can be enhanced by application of historical data comprising pertinent subroutines, and suchlike. Further, an entity can be prompted to provide further information in the event of the input file does not provide all of the content.