JP4349542B2 - Device for detecting telop area in moving image - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a telop area detection device in a moving image, and more particularly to a telop region detection device in a moving image that can extract a telop region at high speed and with high accuracy from information obtained by decoding compressed encoded data itself or only a part thereof. .
[0002]
[Prior art]
As a conventional method for detecting a telop area (hereinafter referred to as a first detection method), in particular, as a telop detection method from a news video, there is a method that uses a temporal luminance distribution difference value for telop detection determination. In addition, a method for obtaining a telop from geometrical properties such as locality of appearance position and regular arrangement, and a method for obtaining a telop from feature amounts as characters such as edge distribution deflection and color similarity have been reported. Further, as a method for analyzing these feature amounts, a telop area detection method incorporating a neural network or a genetic algorithm has been proposed. These methods are methods for extracting a telop area by applying various algorithms to the luminance value of each pixel in a moving image.
[0003]
Also, other telop detection methods have proposed a method that uses encoded data of a moving image that has been compression-encoded, rather than using the pixels themselves. This method achieves a telop area detection process by directly manipulating various parameters and encoded data required at the time of compression.
[0004]
A conventional method (hereinafter referred to as a second detection method) that pays attention to a temporal change in motion prediction error observes temporal variation of motion prediction information for a code unit block in an image and detects an instantaneous appearance of a telop. . Only the minimum necessary information is selected and the telop area is extracted. For this reason, the extracted resolution is set to the size of the encoding unit block of each compression method having motion prediction information.
[0005]
Furthermore, in the method focused on the coding mode of the code unit block (hereinafter, third detection method), the count counter is increased or decreased according to the coding mode from the correlation between the feature of the stationary telop and the coding mode. An area equal to or greater than the threshold is recognized as a telop area candidate, and further extracted as a telop by determining the shape. References disclosing the third detection method include, for example, IEICE Transactions D-II, Vol. J81-D-II No. 8, PP1847-1855, August 1998 “From MPEG Coded Video. "High-speed telop area detection method".
[0006]
[Problems to be solved by the invention]
In order to apply the first detection method to compression-encoded moving image data, it is necessary to once decode the encoded data, and the telop detection process cannot be applied unless the compressed encoded data is returned to the pixel area information. . Therefore, the first detection method is realized by, for example, the configuration shown in the block diagram of FIG.
[0007]
The variable length decoding unit 51 in FIG. 10 receives compressed image encoded data and performs decoding processing such as variable length decoding, inverse quantization, and coefficient range restriction. The variable length decoding unit 51 outputs the decoded frame and block coding mode information, motion prediction information, motion prediction error information, and the like. The input of the image generation unit 52 is prediction error information from the variable length decoding unit 51, and generates image data of one frame through inverse transformation. In addition, the motion compensation unit 52 extracts a block using the motion prediction information from the image memory 53 that holds a motion prediction reference frame, and outputs the image data output from the image generation unit 52 to form a complete frame. to add. This image is input to the telop detection unit 54 and is stored in the image memory 53 if it is a frame that becomes a reference image for the next and subsequent frames. After these series of decoding processes, the telop detection unit 54 performs the telop area detection process in the pixel area for the first time. The detection result by the telop detection unit 54 is sent to the image display unit 55.
[0008]
In the first detection method, there is a problem that a large calculation cost is required for the decoding process of the compressed data and the telop area detection process using the decoded image.
[0009]
On the other hand, since the second and third detection methods use the compressed encoded data itself, the decoding process can be omitted and the detection process can be executed at high speed. However, in actual moving images, motion prediction error information changes greatly due to camera work such as panning and tilting, and video effects edited after shooting such as wipes and dissolves. Is difficult. In particular, this influence is great in scene changes, and the second detection method has a problem that detection accuracy is inferior, such as erroneously recognizing a frame after a scene change as a telop area.
[0010]
Further, the third detection method has a characteristic that the detection rate becomes high when a large number of motion vectors exist outside the telop area. However, in a low-resolution video, the motion vector is relatively small, and the distribution of the encoding mode is also different. Also, news videos and the like often have a fixed camera, and if there is no motion vector in the background, there is a risk of misdetecting an area other than the telop as a telop area.
[0011]
An object of the present invention is to solve the above-described problems of the prior art, and a telop area detection device that can detect the appearance of a telop at high speed and with high accuracy from compressed encoded data itself or information obtained by decoding only a part thereof. Another object of the present invention is to provide a telop area detection device that can extract a telop position in a frame.
[0012]
In order to achieve the above-mentioned object, the present invention provides a telop area detection device in a moving picture that receives compressed moving picture data as input, adds telop area information to the moving picture data, and outputs the same. A variable-length decoding unit that performs variable-length decoding on the compressed moving image data, and a region in which a change is recognized by comparing the current and previous intra-frame encoded image decoded by the variable-length decoding unit. If the change is detected as to whether or not it converges, telop Output candidate location information A time transition determination unit; In the inter-frame encoded image decoded by the variable length decoding unit existing between the intra-frame encoded images, the block corresponding to the position information of the telop candidate Types of encoding modes A block having a coding mode suitable for the telop is extracted from the intra-frame coded image and the position information of the block is output. A telop position determination unit; With respect to the telop candidate block of the inter-frame encoded image, the bidirectional prediction image group output from the variable-length decoding unit Reference direction of motion prediction information Temporal change And an appearance frame determination unit for detecting an appearance frame of a telop.
[0013]
According to this feature, the telop area detection process has been made step-by-step so And High-precision telop area detection processing can be performed.
[0014]
DETAILED DESCRIPTION OF THE INVENTION
The present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing the configuration of an embodiment of the present invention. In this embodiment, MPEG-1 video (ISO / IEC 11172-2), which is an international standard, is used as an input moving image encoding method, but the present invention is not limited to this.
[0015]
As input of the entire system, encoded data of a compressed and encoded moving image is given. Only necessary information is partially decoded by the variable length decoding unit 1 in the encoded data, and the decoded information A, B, and C are respectively converted into a time transition determination unit 2, a telop position determination unit 3, and an appearance frame determination. Sent to part 4. Here, the information A is encoded information of an intra-frame encoded image (I picture) between (n−N) frames and (n + mN) frames, and B is P and B between n frames and (n + mN) frames. Coding mode information of a picture, C is motion prediction information of a B picture between (n−N) frames to n frames. Here, the constant N represents the number of pictures in the GOP and is a parameter indicating the appearance interval of the intra-frame encoded image. N and m are arbitrary positive integers.
[0016]
The time transition determination unit 2 examines the state of temporal transition based on the encoding information A of a plurality of intra-frame encoded images. Then, on the basis of the examination, an area that is a telop area candidate is set on the I picture, and position information D of this area is output to the telop position determination unit 3.
[0017]
The telop position determination unit 3 determines a telop determination target block based on the position information D from the time transition determination unit 2. At the same time, the encoding mode information B of the target block is input from the variable length decoding unit 1, and the selection status of the encoding mode is grasped for each determination target block. Based on these results, a block having an encoding mode suitable for the telop is extracted from the I picture, and the position information E of the block is sent to the appearance frame determination unit 4.
[0018]
The appearance frame determination unit 4 determines a detection target block based on the block position information E input from the telop position determination unit 3 and simultaneously receives the motion prediction information C from the variable length decoding unit 1. Based on the motion prediction information C, frame determination processing is performed to determine from which frame a telop has appeared.
[0019]
The determination result F is output to a detection result display unit or a recording unit (not shown). The detection result display unit or the recording unit outputs the detection result and, if requested, partially decodes and presents the video in the extraction area.
[0020]
Next, the function of the time transition determination unit 2 will be described in detail with reference to the flowchart of FIG. The time transition determination unit 2 performs four processes. These four processes are a line fluctuation determination process in step S1, a block fluctuation determination process in step S2, a convergence determination process in step S3, and a shape shaping process in step S4.
[0021]
The line fluctuation determination process (step S1) is performed on the encoded data of the two intra-frame (Intra) encoded images In-N and In that are input. Here, the constant N represents the number of pictures in the GOP and is a parameter indicating the appearance interval of the intra-frame encoded image. In the line fluctuation determination process, an area that has changed over time is extracted in units of one line of a block. The position information of the area determined as the fluctuation area in the process of step S1 is input to the block fluctuation determination process of step S2. In the block variation determination process, the variation region is determined in units of blocks, and the extracted block is sent to the convergence determination process in step S3.
[0022]
In the convergence determination process, a region where the change converges in all frames In + mN (0 <m <q) after In is extracted from the designated region, and the region is set as a telop region candidate. Here, the constant q represents the number of frames subject to convergence determination, and takes a value of 1 or more. The shape shaping process in step S4 receives the telop area candidate and eliminates the isolated small area in consideration of the size of the telop. Next, the missing part of the telop area candidate is compensated by the expansion / contraction process, and the telop area candidate is shaped for the subsequent determination process. Above, the process of the said time transition determination part 2 is complete | finished.
[0023]
The time transition determination unit 2 pays attention to a region where a change is recognized by comparing the current intra-frame encoded image and the previous intra-frame encoded image, and only the region in the future intra-frame encoded image Whether the change converges at. For the specific occurrence determination of the time change, the DC component and the AC component of the DCT coefficient are individually used as determination criteria.
[0024]
Below, the process of said step S1-S3 is demonstrated in detail with reference to FIGS.
[0025]
First, the line fluctuation determination process in step S1 of FIG. 2 will be described with reference to FIG. FIG. 3A is a flowchart showing details of the line fluctuation determination process using a DC component. In the line fluctuation determination process, DCT coefficient DC component information of the frame In and the frame In-N one GOP before is input. First, assuming that the telop appears horizontally or vertically with respect to the screen, the DC component is read in units of one line each in the vertical and horizontal directions in the process of step S10. For example, as shown in FIG. 3B, the DC component of the DCT coefficient of each block of the frame In and the frame In-N before 1 GOP is read in units of vertical and horizontal lines.
[0026]
In step S11, a coarsely quantized luminance histogram is generated in order to capture a rough change in the DC component. In step S12, the sum of absolute differences from the histogram of the same position line in the past frame In-N is obtained. In step S13, a determination is made based on a threshold value, and for a line having a difference value equal to or greater than the threshold value, the entire line is set as a telop area candidate in step S14. Otherwise, in step S15, the entire line is set as a non-telop area.
[0027]
In step S16, it is determined whether or not the processing for each line has been completed for all blocks. If not, the process returns to step S10, and the series of processing of steps S10 to S15 is repeated for the next line. If the determination in step S16 is affirmative, the process proceeds to step S17.
[0028]
In step S17, the number of lines that are telop area candidates is counted. If the telop area candidates occupy most of the frame, the luminance change due to a cause other than the telop is set as a non-telop area and the current frame is changed. The detection process ends. Otherwise, the position information of the extracted block is output, and the time variation determination process using the DC component is terminated.
[0029]
Next, the block variation determination process in step S2 will be described with reference to FIG. FIG. 4A shows a flowchart of block fluctuation determination processing using an AC component. In the variation determination process, DCT coefficient AC component information of the frame In and the frame In-N is input and processed in units of blocks. Since the edge region interwoven with the character and the background corresponds to the amount of the DCT coefficient AC component, a block whose change in the partial sum of the blocks exceeds the threshold both spatially and temporally is defined as a telop region.
[0030]
In step S19, it is checked whether the target block is an area determined as a telop area candidate in the line fluctuation determination process in step S1. If it is a telop area candidate, the processing is continued. Otherwise, the non-telop is determined and the determination for the block is ended. In step S20, an absolute value partial sum of AC components is calculated for the telop area candidate.
[0031]
FIG. 4B shows an example of the coefficient range used for variation determination. Here, for the DCT coefficient AC component, the determination based on the absolute value partial sum of nine AC low-frequency components in a zigzag scan order is used.
[0032]
In step S21, a difference between the absolute position partial sum of nine AC low frequency components of the same position block in the past frame (In-N frame) is calculated. In step S22, determination based on a threshold is performed, and a block having a difference value equal to or greater than the threshold is determined as a telop area candidate in step S23. Otherwise, it is determined as a non-telop area candidate in step S24. In step S25, it is determined whether or not the processing has been completed for all the blocks. If not completed, the process returns to step S19 to repeat the series of processing in steps S19 to S24. If it is determined in step S25 that all blocks have been processed, the AC component variation determination process ends.
[0033]
Next, details of the convergence determination process in step S3 will be described with reference to FIG. FIG. 5A shows a flowchart of the convergence determination process. There is a high possibility that the fluctuation area is the appearance of a telop, but there is a possibility that the fluctuation area is a fluctuation due to a moving object or camera work. In the telop, the temporal luminance fluctuation is severe in the appearance transition period, but the luminance change hardly occurs in the steady state. Therefore, in the convergence determination process, continuity with respect to the position of the telop is used in order to remove the variation area caused by factors other than the appearance of the telop from the telop area candidates extracted in the steps S1 and S2.
[0034]
Specifically, after confirming that there is no scene change or the like based on the temporal change of the DC component for the entire screen, the direction and position of the edge of the stationary telop is the same as the telop area candidate. Is used. For edge matching, class classification using a partial sum of AC components is used. For example, when the nine AC components shown in FIG. 4 (b) are further divided into three parts of vertical (vertical), horizontal (horizontal), and diagonal elements, four blocks are obtained as shown in FIG. 5 (b). Thus, a total of 12 classes can be formed.
[0035]
DCT coefficient AC component information from frame In to frame In + qN is input to the convergence determination process in step S3. In step S26, it is checked whether or not the target block is a telop area candidate. If it is a telop area candidate, the process is continued. Otherwise, the non-telop area is selected and the convergence determination process for the block is terminated. In step S27, the edge class of the target block in the frame In is determined. For example, an edge class having the maximum partial sum is obtained from the 12 classes shown in FIG. In step S28, the same edge class of the same position block in the frame In + mN (0 <m <q) is determined. In general, since intra-frame encoded images are often arranged at intervals of 12 to 15 frames, at 30 fps, they are arranged at intervals of approximately 0.5 seconds. Assuming that a telop is presented for 2 seconds or more, the value of q can be set to about 4.
[0036]
In step S29, it is determined whether or not the partial sums of the edge classes obtained in steps S27 and S28 match. If they match, the block is set as a telop area candidate in step S30. Otherwise, it is determined as a non-telop area candidate in step S31. In step S32, it is determined whether or not the processing has been completed for all the blocks. If not, the processing returns to step S26, and the series of processing in steps S26 to S31 is repeated. If the processing of all blocks is completed, the convergence determination process by class classification is terminated.
[0037]
As a result of the above time transition determination processing, a region that is a telop region candidate is set on the I picture.
[0038]
Next, the function of the telop position determination unit 3 (see FIG. 1) based on the coding mode information will be described with reference to FIG. The telop position determination unit 3 receives the telop area candidate information extracted by the time transition determination unit 2. At the same time, encoding mode information of a frame (P, B picture) existing between the frame In and the frame In + mN is input from the variable length decoding unit 1. A group of blocks existing at the same position is processed as a unit over a plurality of frames. The verification of the telop using the encoding mode information is limited to the telop area candidates extracted by the above-described detection process.
[0039]
In step S33, it is determined whether or not the target block is determined as a telop area candidate by the time transition determination unit 2. If it is a telop area candidate, the processing is continued. Otherwise, the non-telop is determined and the determination for the block is ended. A step S34 generates a count counter from the inter-frame distance referred to by the encoding mode information and the motion prediction information. In step S35, the counter counted in step S34 is determined based on a threshold value. A block group in which a counter having a threshold value or more is formed is set as a telop area candidate in step S36. Otherwise, it is set as a non-telop area candidate in step S37. In step S38, it is determined whether or not the processing has been completed for all the blocks. If not completed, the process returns to step S33, and the series of processing in steps S33 to S37 is repeated. If the processing of all the blocks has been completed, the process proceeds to step S39. In step S39, shape shaping processing is performed on the telop area candidate. The processing content is the same as the shape shaping processing unit (step S4). Thus, the determination process using the encoding mode information is completed.
[0040]
Frame coding information and block coding information are used as coding mode information which is one of input information. There are the following three types of frame encoding information.
(1) Intra-frame coded image (I picture)
(2) Forward prediction image (P picture)
(3) Bidirectional prediction image (B picture)
[0041]
The block coding mode includes an intra-frame coding block (Intra) and an inter-frame coding block (Inter). Furthermore, there are the following four types of inter-frame coding blocks depending on the presence or absence of motion compensation and coding.
(1) Motion compensated coding block (MC coded)
(2) Frame differential coding block (no MC coded)
(3) Motion compensation block (MC no coded)
(4) Skipped block (Skip)
However, there are three types of motion prediction: forward direction, reverse direction, and both directions.
[0042]
At this time, there is a high correlation between the feature of the stationary telop and the coding mode of the corresponding block. For example, motion prediction information does not exist in a stationary telop or its size is close to zero. In addition, as a characteristic of the character string constituting the telop is the edge of the boundary, the motion prediction error information is rarely omitted because there is a complex texture.
[0043]
Therefore, the no MC coded coding mode having the above features is most likely a telop. However, when considering the encoding process of the real video, the motion prediction information is not given to the still region as the accuracy of the encoder is improved. That is, a mode having no motion prediction information is often selected regardless of the presence or absence of a telop. In addition, motion prediction information may not be assigned because the apparent motion is small even in an area that is moving as the motion prediction reference frame is closer.
[0044]
As a method for solving this problem, the concept of temporal distance is introduced and used as reliability information of the coding mode when making a determination in the coding mode. If the reference frame is close, even if there is no motion prediction information, the possibility of it being a telop is not guaranteed, so the reliability of the coding mode information is set low. On the other hand, if motion prediction information exists, the reliability as a non-telop area candidate is increased because there is a clear moving object. On the other hand, if the reference frame is far away, the opposite setting is prepared. That is, when there is no motion prediction information, it can be determined that the area is completely stationary, so the reliability of the encoding mode information as a telop area candidate is set high. Even if motion prediction information exists, the reliability of the coding mode information as a non-telop area candidate is set low.
[0045]
An example of the counting method using the encoding mode information with the temporal distance as reliability information (step S34) will be described with reference to the flowchart of FIG. The input information is the encoding mode information of the block group at the same position.
[0046]
In step S40, the distance to the frame referenced by the motion prediction information is calculated. However, when the prediction method is bi-directional prediction, the closest one is adopted. In step S41, a determination is made using the coding mode information of the block. If the block coding type is MC coded or MC no coded with motion prediction information, a number inversely proportional to the temporal distance to the reference frame obtained in step S40 is subtracted in step S42. On the other hand, if Intra has no motion prediction information, no MC coded has a motion prediction information size of 0, or Skip, a number proportional to the temporal distance is added in step S43. In step S44, it is determined whether or not the processing has been completed for the block existing at the same position. If the processing has not been completed, a series of operations from step S40 is repeated for the next block. Otherwise, the counter counting ends.
[0047]
By the above telop position determination process, a block having an encoding mode suitable for the telop can be extracted from the I picture.
[0048]
Next, the operation of the appearance frame determination unit 4 will be described. The verification of the telop using the motion prediction information is limited to the telop area candidates extracted by the above-described detection process. Here, the coding mode of the block and the temporal reference direction of the motion vector are used. When a telop appears, the following properties appear in the telop area of consecutive B pictures (hereinafter referred to as B picture groups) divided into I or P pictures.
(1) There is no bidirectional prediction in the B picture group.
(2) When the appearance frame is an I or P picture, only the forward motion vector exists in the B picture group.
(3) When the appearance frame is a B picture, a backward motion vector also exists in the B picture group.
(4) When the appearance frame is a B picture, there is only one forward / reverse switching in the B picture group.
(5) No motion vector after telop appears.
[0049]
In order to facilitate understanding of the above properties, FIG. 9 is shown. From FIGS. 7A and 7B, it is clear that when a telop appears in a B picture, I picture, or P picture, there is no bidirectional prediction in the B picture group as in (1). In addition, when the telop appearance frame is an I or P picture, it is clear from FIG. 4B that only the forward motion vector exists in the B picture group as in the above (2). In addition, when the telop appearance frame is a B picture, it is clear from FIG. 5A that the B picture group has the properties (3) and (4). As shown in FIG. 5C, when bi-directional prediction exists in the B picture group, no telop appears in any of the I, P, and B picture groups.
[0050]
Therefore, the appearance frames of the telop are narrowed down to the frames satisfying the above conditions (1) to (5) from the motion prediction information of the B picture group. Note that both sides of the B picture group in FIG. 9 may both be P pictures.
[0051]
Specifically, when the appearance of a telop is detected in a plurality of intra-frame encoded images by the time transition determination unit 2, the appearance frame determination unit 4 verifies the above characteristics (properties) for the B picture group inside the GOP. . First, for each B picture group, the temporal reference direction of motion prediction information is examined for each block. When the B picture group is configured only by forward prediction (the property 2), it is determined that a telop has appeared in the immediately following I or P picture. When the B picture group includes the reverse direction, or when the change from the forward direction to the reverse direction exists only once (the properties 3 and 4), it is determined that a telop has appeared in the B picture in which the reverse direction has started. In other cases, it is determined that no telop appears in the continuous B picture group, and the determination process is continued for the next B picture group. Thereby, the appearance frame of the telop can be detected in units of frames.
[0052]
However, since a stationary telop is assumed, the length of the motion prediction information itself is limited to a block having almost zero. Blocks with significant motion prediction information are excluded from telop area candidates regardless of the reference direction. Similarly, the length of the motion prediction information is verified for each block at the same position for the GOP after the telop appearance is determined. If the length is not sufficiently close to 0, the block is excluded from the telop area candidates.
[0053]
FIG. 8 shows a flowchart of the operation of the appearance frame determination unit 4 based on motion prediction information. The position information of the telop area candidate is input from the telop position determination unit 3. At the same time, the motion prediction information of the frame between the frame In-N and the frame In is input from the variable length decoding unit 1. The determination is made on individual blocks of the B picture group.
[0054]
In step S45, it is determined whether or not the target block is determined as a telop area candidate in the frame In by the telop position determination unit 3. If it is a telop area candidate, the process is continued, otherwise the determination for the block group is ended. In step S46, the characteristics of the B picture group accompanying the appearance of the above-mentioned telop are verified (refer to the characteristics (1) to (5) and FIG. 9). In step S47, it is determined whether or not the output of step S46 satisfies the above property. If so, the B picture frame or the I or P picture in which the backward vector appears in step S48. Outputs the frame as a telop appearance frame. Otherwise, in step S49, the block is set as a non-telop, and it is determined that no telop appears in the B picture group. In step S50, it is determined whether the determination process has been completed for all blocks in the B picture group. If not completed, the process returns to step S45, and the series of processes of steps S45 to S49 is repeated for the next block. Otherwise, the determination process is continued.
[0055]
In step S51, it is determined whether the determination process has been completed for all the B picture groups in the GOP. If not completed, the series of processing in steps S45 to S50 is repeated for the next B picture group. Otherwise, the process ends. If no telop start frame is detected in step S48, all blocks are set as non-telop areas, and the process of the appearance frame determination unit 4 ends. In this case, the appearance frame determination unit 4 then performs the determination process of FIG. 8 again for all the B picture groups in the next GOP.
[0056]
As is apparent from the above description, according to the present invention, the following features (1) to (5) can be provided.
(1) Since the telop area detection process is made stepwise, both high-speed processing and high-precision processing can be achieved.
(2) Since the temporal variation determination and the subsequent convergence determination are performed, an unnecessary variation region can be eliminated and the telop region can be detected.
(3) Blocks having significant motion prediction information can be excluded from detection targets.
(4) In consideration of the reliability of the coding mode information, detection determination by weighting counting can be performed.
(5) Using the motion prediction information, the telop detection resolution can be achieved in units of one frame.
[0057]
【The invention's effect】
As is apparent from the above description, according to the present invention, in addition to partial decoding of compression-coded moving image data, frames (for example, intra-frame encoded images) having an interval of 10 or more frames are provided. ), The detection processing of the telop start frame is made hierarchical, such that detection is first performed and then detection is performed in units of one frame, so that the conventional pixel area detection method (the first detection method described above) Of course, the processing cost can be reduced even when compared with the detection methods in the code data region (the second and third detection methods). In other words, in the present invention, the application range of the telop detection determination can be minimized, so that the processing amount of the telop area extraction method on the compression encoded data can be further reduced and the high speed can be further improved. Become.
[0058]
Further, according to the present invention, the two characteristics of the precursor (variation) associated with the appearance of the telop and the continuity (convergence) after the appearance are determined by different discriminating methods. Much better detection accuracy can be achieved.
[0059]
In the present invention, since the encoding mode information is used to improve the accuracy of blocks that are telop area candidates and the motion prediction information is used to obtain the telop start frame, the telop detection resolution can be increased. become.
[Brief description of the drawings]
FIG. 1 is a block diagram showing a schematic configuration of an embodiment of the present invention.
FIG. 2 is a flowchart showing an operation of a time transition determination unit in FIG. 1;
FIG. 3 is a flowchart and an explanatory diagram showing details of the line fluctuation determination process (step S1) in FIG. 2;
FIG. 4 is a flowchart and an explanatory diagram showing details of a block fluctuation determination process (step S2) in FIG. 2;
FIG. 5 is a flowchart and an explanatory diagram showing details of convergence determination processing (step S3) in FIG. 2;
6 is a flowchart showing the operation of the telop position determination unit in FIG. 1. FIG.
7 is a flowchart showing details of the weighted encoding mode counting process (step S34) of FIG. 6;
FIG. 8 is a flowchart showing the operation of the appearance frame determination unit in FIG. 1;
FIG. 9 is an explanatory diagram of the appearance predictor verification process (step S46) of FIG. 8;
FIG. 10 is a block diagram showing a configuration of a conventional first detection method.
[Explanation of symbols]
DESCRIPTION OF SYMBOLS 1 ... Variable length decoding part, 2 ... Time transition determination part, 3 ... Telop position determination part, 4 ... Appearance frame determination part.

Claims (17)

In a telop area detection device in a moving image that receives compressed moving image data, adds telop area information to the moving image data, and outputs the telop area information.
A variable length decoding unit for variable length decoding the compressed moving image data;
When it is detected that the change converges in the area where the change is recognized by comparing the current decoded by the variable length decoding unit with the previous intra-frame encoded image, and the change is detected. A time transition determination unit that outputs position information of telop candidates to
In the inter-frame encoded image decoded by the variable length decoding unit existing between the intra-frame encoded images, the encoding mode suitable for the telop is determined from the type of the encoding mode of the block corresponding to the position information of the telop candidate. A telop position determination unit that extracts a block having the encoded image from the intra-frame encoded image and outputs position information of the block ;
Appearance frame determination for detecting an appearance frame of a telop from a temporal change in a reference direction of motion prediction information of a bidirectional prediction image group output from the variable length decoding unit for the telop candidate block of the inter-frame encoded image A telop area detecting device in a moving image. The telop area detection device in a moving image according to claim 1,
The time transition determination unit uses a difference value of motion prediction error information between frames as a determination criterion as a telop appearance determination. The telop area detection device in a moving image according to claim 2,
The time transition determination unit uses a histogram difference based on a DCT coefficient DC component of motion prediction error information as a difference value between frames used for variation determination. The telop area detection device in a moving image according to claim 2 or 3,
The time transition determination unit uses a histogram difference of motion prediction error information for each line of a block, both vertically and horizontally, as a telop area detecting device. The telop area detection device in a moving image according to claim 2,
The time transition determination unit uses a difference based on a partial absolute value sum of DCT coefficient AC components of motion prediction error information as a difference value between frames used for variation determination. The telop area detection device in a moving image according to claim 1,
The telop area detection device, wherein the time transition determination unit includes means for confirming a steady state after the telop appears. The telop area detection device in a moving image according to claim 6,
The telop area detection device according to claim 1, wherein the time transition determination unit uses identity determination by class classification for confirmation of a steady state. The telop area detection device in a moving image according to claim 6 or 7,
The telop area detection device, wherein the time transition determination unit forms a class used for grasping a steady state based on uneven distribution of coefficient distribution of motion prediction error information. The telop area detection device in a moving image according to any one of claims 6, 7, and 8,
The time transition determination unit uses the edge direction identified from the three elements of the vertical, horizontal, and diagonal motion prediction error information DCT coefficient AC component for the formation of a class used for convergence determination. . The telop area detection device in a moving image according to claim 1,
The telop position detection unit uses a 0 approximation determination based on the size of motion prediction information as a determination reference for determining a telop. The telop area detection device in a moving image according to claim 1 ,
The telop position determination unit uses a temporal distance to a reference frame of motion prediction information for determination of reliability with respect to encoding mode information. The telop area detection device in a moving image according to claim 11 ,
A telop area detection apparatus using a weighting coefficient counter for determining reliability of the encoding mode information. The telop area detection device in a moving image according to claim 12 ,
The weighting factor of the weighting factor counter, telop area detection device, characterized in that made proportional to the temporal distance to the frame motion prediction information refers. The telop area detection device in a moving image according to claim 1 ,
The appearance frame determination unit uses, as a determination criterion, that there is no bidirectional motion prediction information in a telop area in a continuous bidirectional prediction image as a determination of a telop appearance frame. . The telop area detection device in a moving image according to claim 1 ,
When the telop appears in the intra-frame encoded image or the unidirectional prediction image as the determination of the telop appearance frame, the appearance frame determination unit predicts the forward motion in the telop area in the previous continuous bidirectional prediction image. A telop area detection apparatus using, as a criterion, the presence of only information. The telop area detection device in a moving image according to claim 1 ,
The appearance frame determination unit determines, as a determination criterion, that when the telop appears in the bidirectional prediction image, the backward motion prediction information also exists in the telop area in the continuous bidirectional prediction image as the determination of the appearance frame of the telop. A telop area detection apparatus characterized by being used. The telop area detection device in a moving image according to claim 1 ,
When the telop appears in the bidirectional prediction image, the appearance frame determination unit determines that the forward / reverse direction of the motion prediction information is switched only once to the telop area in the continuous bidirectional prediction image. A telop area detection apparatus characterized by being used as a criterion.

Images