CN101909143A - Image detection device and method - Google Patents

Abstract

An image detection apparatus adapted to receive a video stream including at least one frame, each frame including a plurality of columns of data, each column of data having a plurality of pixels, and each frame representing an image and a matte, the image detection apparatus comprising: a characteristic unit for sequentially receiving the plurality of pixels to determine a pixel characteristic value for each pixel; and a searcher comprising: the image comparator is used for measuring the pixel characteristic value of the current pixel so as to judge whether the current pixel belongs to the image or not; and a mask comparator for measuring the pixel characteristic value of the current pixel to determine whether it belongs to a mask; the searcher estimates the image position based on the determinations of the image comparator and the mask comparator. An image detection method is also disclosed.

Description

Image detection device and method

technical field

The present invention relates to video processing technology, in particular to an image detection device and method for identifying image positions.

Background technique

Digital TV provides a wide screen size of 16:9, which can effectively expand the viewing field of view, making viewers feel as if they are in the picture. Since traditional analog TVs mostly produce video images with an aspect ratio of 4:3, they must be processed through appropriate conversion ratios before they can be displayed on wide-screen TVs. Similarly, if you want to watch a high-quality video picture produced in a 16:9 ratio through a traditional analog TV, you also need a corresponding conversion ratio.

Referring to Figure 1, the general scaling process will scale the original image 7 with the most appropriate ratio, but usually it cannot fully match the ratio of the desired format. At this time, the method of increasing black shading is often used to make up for the shortcomings. Therefore, video frame 8 generally includes image content 81 and border content 82 .

One of the video scanning methods is interlaced scanning, which refers to dividing each picture into an even field and an odd field for transmission. When the multimedia chip receives the video, it performs de-interlace processing and presents it on the display panel. The de-interlacing process usually selects multiple adjacent image fields for dynamic compensation and interpolation. If the positions of the image 81 and the masking edge 82 are not known in advance, and the image 81 of one field and the masking edge 82 of the other field are mistakenly processed, it will lead to incorrect dynamic compensation and incorrect interpolation. expected result.

In addition, when the multimedia chip performs other image processing that requires feedback (feedback) operations, since the current field/frame must be compared with the previous field/frame, it may cause cross-processing of the image 81 of one field/frame and the image 81 of another field/frame. The edge 82 is masked, resulting in artifacts, such as noise processing. Therefore, prior to de-interlacing or other image processing, it is necessary to know the position of the image 81 and the position of the masking edge 82 in advance.

Contents of the invention

Therefore, the object of the present invention is to provide an image detection device and method that can identify the image position and the masking position.

Therefore, the image detection device of the present invention is suitable for receiving a video stream comprising at least one frame, each frame includes multiple columns of data, and each column of data has multiple pixels, and each frame presents an image and a masking edge, the image detection The device includes: a characteristic unit, which receives the plurality of pixels in order to determine a pixel characteristic value for each pixel; and a searcher, including: an image comparator, which measures the pixel characteristic value of the current pixel to determine whether it belongs to an image; and The edge comparator measures the pixel characteristic value of the current pixel to determine whether it belongs to shading; the searcher estimates the image position based on the image comparator and the judgment of the shading comparator.

The image detection method of the present invention is applicable to a video stream containing at least one frame, each frame includes multiple columns of data, and each column of data has multiple pixels, and each frame presents an image and a shading edge, the image detection method includes the following Steps: determining a pixel characteristic value for each of the pixels; measuring the pixel characteristic value of the current pixel to determine whether it belongs to an image; measuring the pixel characteristic value of the current pixel to determine whether it belongs to masking; and according to the judgment The result infers the image position.

Description of drawings

Fig. 1 is a schematic diagram illustrating that the original picture is scaled with an appropriate ratio to present the video picture to be produced;

Fig. 2 is a block diagram of a first preferred embodiment of an image detection device of the present invention;

Fig. 3 is a schematic diagram illustrating the search range of this preferred embodiment;

Fig. 4 (a)～(d) are schematic diagrams, illustrating the relative positional relationship of the characteristic values used by each search method of this preferred embodiment;

Fig. 5 is a flowchart of a first preferred embodiment of an image detection method of the present invention; and

FIG. 6 is a flow chart illustrating the verification procedure of the upper verification unit of the preferred embodiment.

[Description of main component labels]

1 feature unit 2 searcher

21 upper search unit 211 image comparator

212 Masking Comparator 213 Judger

22 lower search unit 221 image comparator

222 Masking comparator 223 Judger

23 left search unit 231 image comparator

232 Masking Comparator 233 Judger

24 right search unit 241 image comparator

242 Masking Comparator 243 Judger

3 Validator 31 Upper confirmation unit

32 Down Confirmation Unit 33 Left Confirmation Unit

34 right acknowledgment unit 4 column buffers

61～65 Steps 611～612 Substeps

621～622 Substeps 641～644 Substeps

61’～64’ steps 61”～64” steps

Detailed ways

The aforementioned and other technical contents, features and functions of the present invention will be clearly presented in the following detailed description of two preferred embodiments with reference to the drawings.

Before the present invention is described in detail, it should be noted that in the following description, similar elements are denoted by the same reference numerals.

first preferred embodiment

Referring to Fig. 2, the image detection device of the present invention is suitable for receiving a video stream comprising a plurality of pictures, the resolution of each picture is M×N, including N columns of data (for example: the 1st column, the 2nd column...the nth column column...), and each column of data has M pixels (for example: 1st pixel, 2nd pixel...mth pixel...). This preferred embodiment includes a characteristic unit 1 , a searcher 2 and a validator 3 . The searcher 2 includes an upper search unit 21, a lower search unit 22, a left search unit 23 and a right search unit 24, and each search unit 21, 22, 23, 24 includes an image comparator 211, 221, 231, 241, a cover Edge comparators 212 , 222 , 232 , 242 and judgers 213 , 223 , 233 , 243 . The validator 3 includes an upper validating unit 31 , a lower validating unit 32 , a left validating unit 33 and a right validating unit 34 .

The feature unit 1 receives the upper search end position reg_SEARCH_U, the lower search start position reg_SEARCH_D, the left search end position reg_SEARCH_L and the right search start position reg_SEARCH_R, and can thereby define the upper search range, lower search range, and left search range of each frame and the right search range, as shown in Figure 3.

The characteristic unit 1 also sequentially receives the pixels in each search range and the pixels delayed by a line buffer (linebuffer) 4, and calculates the pixel characteristic value of each pixel to output the upper characteristic value U and the lower characteristic value D , the current characteristic value C, the left characteristic value L, and the right characteristic value R. The positional relationships of the corresponding pixels in the upper, lower, left, and right search ranges are shown in Figure 4(a)-(d) respectively.

In this embodiment, each pixel is divided into a luminance component y and two chroma components u, v, and the pixel characteristic value of each pixel is set as (1/4)·(2y+|u|+| v|), where u and v are both signed data types, and |X| represents the absolute value of X. This is because the luminance component y is the main factor determining the characteristics of the pixel, so it is given a larger weight.

However, the basis vectors of the pixels may also be formed by selecting other basis vectors, which is not limited thereto. In addition to the above-mentioned set values, the pixel characteristic value may also be expressed by other expressions that can highlight the characteristics of the pixel, and the present invention is not limited thereto.

The image detection device of the present invention can detect image positions from the upper, lower, left and right search ranges respectively. Here, the detection method of the upper search range, that is, the upper search method, will be described first.

search method

Referring to Fig. 5, the upper search method performed by the first preferred embodiment of the image detection method of the present invention includes the following steps:

Step 61: The image comparator 211 evaluates each group of data in the upper search range (in this embodiment, each group refers to each row) to infer a first up-estimated position representing the start row of the image.

And step 61 comprises following sub-steps:

Sub-step 611: The image comparator 211 calculates the number of pixels in a current row of data that are evaluated as images. When the current characteristic value C does not fall within the range defined by the maximum shading value reg_BLANK _max and the minimum shading value reg_BLANK _min , it is estimated that the corresponding pixel is an image pixel. At this time, the image comparator 211 adds 1 to the upper image count IMAGE_U_cnt , such as equation (1). This is because the luminance of masking is usually low-level, but not extremely black (ie, zero luminance).

IF((C＞reg_BLANK _max )||(C＜reg_BLANK _min ))

IMAGE_U_cnt++ (1)

Sub-step 612: The image comparator 211 compares whether the upper image count IMAGE_U_cnt is greater than a horizontal image judgment reg_H_IMAGE (for example, 3/4 of the number of pixels in each row of data), so as to estimate the first estimated position.

If the result is yes, it is assumed that the current column data (assumed to be the nth column) is the image start column, and the first estimated position is evaluated as the nth column (as shown in equation (2)), and skip to step 63 . If not, the first up-estimated position is not output, and the up-image count IMAGE_U_cnt is reset to zero, and jumps back to sub-step 611 until the evaluation of the up-search range is completed.

IF(IMAGE_U_cnt＞reg_H_IMAGE)

return(n) (2)

Step 62: The shading comparator 212 evaluates each group of data in the upper search range (in this embodiment, each group refers to each row), to guess which row the shading ends at, to output a representative image start The second upestimated position of the column. Preferably, step 61 and step 62 are performed simultaneously.

And step 62 comprises following sub-steps:

Sub-step 621: the shading comparator 212 calculates the number of pixels evaluated as shading in a current column of data. When the relationship between the difference between the current characteristic value C and the adjacent characteristic values L, D and a similar difference value reg_ALIKE and a different difference value reg_DIFFER satisfies the equation (3), it means that the pixel corresponding to the current characteristic value C and the left pixel The feature is similar to that of the lower pixel, so it is estimated that the corresponding pixel is a shading pixel. At this time, the shading comparator 212 adds 1 to an upper shading count BLANK_U_cnt.

IF((|C-L|≤reg_ALIKE)&&(|C-D|≥reg_DIFFER))

BLANK_U_cnt++ (3)

Sub-step 622: The shading comparator 212 compares whether the upper shading count BLANK_U_cnt is greater than or equal to a horizontal shading judgment reg_H_BLANK (for example: 3/4 of the number of pixels in each column of data) to estimate the second upper estimated position.

If the result is yes, it is speculated that the nth column may be the edge-shading end column, and the second up-estimated position is determined as the n+1th column (as shown in equation (4)), and skips to step 63 . If not, the second up-estimated position is not output, and the lower image count IMAGE_D_cnt is reset to zero, and jumps back to sub-step 621 until the upper search range is evaluated.

IF(BLANK_U_cnt≥reg_H_BLANK)

return(n+1) (4)

Step 63 : During the processing of the upper search range, the determiner 213 synthesizes the estimations of the comparators 211 and 212 row by row to determine an upper rough estimation position ROUGH_U representing the start row of the image.

There are three conjectures:

Case 1: When the determiner 213 receives the first up-estimated position, it regards it as the rough-up-estimated position ROUGH_U, regardless of the second up-estimated position; this also means that if the up-estimated positions are received at the same time, It will still be updated with the first estimated position.

Situation 2: When the determiner 213 does not receive the first estimated position and receives the second estimated position, it takes the second estimated position as the roughly estimated position ROUGH_U;

Situation 3: When both are not received, the upper rough estimated position ROUGH_U is not updated, and skip to step 65 .

It is worth noting that case 1 is implemented for two reasons. One is that when processing the current column (column n), if the first and second up-estimated positions are received at the same time (equations (2), (4) hold), these values will be n and n+1 respectively. For the upper search range, it is desired to obtain the image start row that appears earlier, so the first up-estimated position is used as the output.

The other reason is that if the nth row is a pure red image and the pixel characteristics of the n+1th row are quite different, the edge shading comparator 212 may misjudge the nth row as the shading end column. However, as long as it is a general image, most of the equations (1) and (2) can be established, so the reliability of the image comparator 211 is relatively high. Therefore, in this embodiment, the first up-estimated position is used to update the upper rough-estimated position ROUGH_U.

Step 64: The upper confirming unit 31 confirms whether the upper roughly estimated position ROUGH_U is indeed an upper exact position EXACT_U representing the start column of the image.

Referring to Fig. 6, and the confirmation procedure of step 64 comprises following sub-steps:

Sub-step 641: the upper confirming unit 31 evaluates whether the upper roughly estimated position ROUGH_U is reasonable. If not, keep the exact position EXACT_U, and go to step 65; if yes, go to sub-step 642.

A possible implementation of the upper confirmation unit 31 is, for example, in a specific application, the known image position starts approximately from the 26th line of a picture, and the upper confirmation unit receives a reasonable value reg_REASON_U of 20 for the upper position, To indicate that after the 20th line is a reasonable detection of the image position. If the received upper rough estimate position ROUGH_U is 9, it is judged as unreasonable.

Another possible implementation is that the upper confirming unit 31 has a pixel averager capable of summing and averaging the current characteristic value C of the column data. If the column data average value corresponding to the upper rough estimation position ROUGH_U does not belong to the image (that is, falls within the range defined by the maximum and minimum shading values reg_BLANK _max , reg_BLANK _min ), then the upper confirming unit 31 determines that it is unreasonable.

Sub-step 642: the upper confirming unit 31 judges whether the upper rough estimated position ROUGH_U is the same as the confirmed upper exact position EXACT_U. If yes, keep the upper exact position EXACT_U, and skip to step 65 . If not, skip to sub-step 643 .

Sub-step 643: The upper confirmation unit 31 judges whether the upper rough estimated position ROUGH_U is the same as an upper tentative position. If not, keep the upper exact position EXACT_U, and the above rough estimated position ROUGH_U is the updated upper tentative position TEMP_U, and set a tentative count to zero, and go to step 65 ; if yes, go to sub-step 644 .

Sub-step 644: the upper confirmation unit 31 determines whether the provisional count is greater than a provisional count threshold. If not, maintain the upper exact position EXACT_U, and increase the tentative count by 1; if yes, use the upper tentative position as the updated upper exact position EXACT_U.

Step 65: Repeat steps 61 to 64 to perform an up search procedure on the next frame until the image detection device stops receiving the video stream.

The reason for performing step 64 is that the possibility determiner 213 receives that the value of the upper rough estimate position ROUGH_U is unstable each time, so when the value changes, the value after the change is recounted. The upper exact position EXACT_U is officially updated as the upper rough estimated position ROUGH_U until the number of consecutive repeated occurrences of the same size value is greater than the provisional counting threshold.

down search

In the first preferred embodiment of the image detection method of the present invention, the following search method is used to detect the end row of images in the search range.

Step 61' is that the image comparator 221 guesses whether the current group (in this embodiment, the current group refers to the nth column) is an image column by calculating the number of image pixels (i.e., the lower image count IMAGE_D_cnt), so as to output a first Estimate the position (column n), as in equations (5), (6). And a test is performed on the entire lower seek range to get the image end column.

IF((C＞reg_BLANK _max )||(C＜reg_BLANK _min ))

IMAGE_D_cnt++ (5)

IF(IMAGE_D_cnt＞reg_H_IMAGE)

save(n) (6)

Step 62' is that the border comparator 222 guesses whether the current group (in this embodiment, the current group refers to the nth column) is the start of the border by calculating the number of border pixels (i.e. the count BLANK_D_cnt of the lower border) column to output a second down-estimated position (column n-1), such as equations (7), (8).

IF((|C-L|≤reg_ALIKE)&&(|C-U|≥reg_DIFFER))

BLANK_D_cnt++ (7)

IF(BLANK_D_cnt≥reg_H_BLANK)

save(n-1) (8)

And the action of the judger 223 of step 63' is similar to the judger 213 of step 63, this is based on the lower search range, what is expected to be the end of the image that occurs later, and the image comparator 221 evaluates whether it is The reliability of image pixels is relatively high, so the first estimated position is the priority output. In addition, the confirmation method of the lower confirmation unit 32 is the same as that of the upper confirmation unit 31 , so it will not be further described.

Left/Right Search Method

In the left search range, the positions of the characteristic values C, R, U are respectively replaced with the positions of the characteristic values C, D, L in the upper search range. In the right search range, the positions of the characteristic values C, L and U are respectively replaced by the positions of the characteristic values C, U and L in the lower search range. And it is implemented in a 45-degree mirroring manner relative to the up/down search method, so details will not be described here.

Second preferred embodiment

The second preferred embodiment uses a left/right search method different from that of the first preferred embodiment. Here, the left search method will be described first.

left search method

The action of the left confirmation unit 33 in step 64" is similar to the first preferred embodiment, so this paragraph only introduces the action of the left search unit 23 (step 61 "～step 63"). Wherein, the image comparator of step 61 " 231 is used to infer which line the image starts at, and the shading comparator 232 in step 62" is used to infer which line the shading ends in, and the judging unit 233 in step 63" synthesizes the guesses of these comparators 231, 232 to roughly estimate Image start line.

_The image comparator 231 evaluates each group of data in the _left search range (in this embodiment, each group refers to Each row) to guess which row the image starts on. It detects point-by-point along the pixels of the current row of data until (C>reg_BLANK _max )||(C<reg_BLANK _min ) is established or the left search range ends, that is, the point-by-point detection of the current row is stopped, and the established position is compared with One left guesses the image position, and the comparison method is as follows:

Case 1: When the established position is less than a left estimated image position, set a left image count IMAGE_L_cnt to 1, and use the established position to update the left estimated image position recorded in the current frame;

Case 2: When the two positions are equal, add 1 to the left image count IMAGE_L_cnt, and maintain the estimated left image position recorded in the current frame;

Case 3: When it is greater than 1, the left image count IMAGE_L_cnt is decremented by 1, and the estimated left image position recorded in the current frame is maintained. However, if the result after subtracting 1 is 0, the image comparator 231 will reset the left image count IMAGE_L_cnt to 1, and update the estimated left image position recorded in the current frame with the established position.

Next, compare whether the left image count IMAGE_L_cnt is greater than a vertical image judgment reg_V_IMAGE. If the comparison result is yes, the image comparator 231 also compares the left estimated image position of the current frame and the previous frame, selects the smaller one as the update value, and regards the update value as a first left estimate position, and generates a value of 1 The first left significant signal of the value. If the comparison result is negative, maintain the left estimated image position of the previous frame, and set the first left significant signal to be 0.

On the other hand, the blanking comparator 232 is based on the relationship between the characteristic values C, U, R and the similarity difference reg_ALIKE, the difference difference reg_DIFFER and a reference blanking value reg_BLANK _ref to evaluate each group of the left search range The data (in this embodiment, each group means each row) is guessed at which row the shading ends. It is roughly the same as the operation of the image comparator 231, except that the point-by-point detection condition is (|CU|≤reg_ALIKE)&&(|CR|≥reg_DIFFER)&&(C<reg_BLANK _ref ), and finally the update value is added to 1 to output a second left estimated position, and output a corresponding second left valid signal.

The determiner 233 synthesizes the outputs of the comparators 231 and 232 to infer a rough left position ROUGH_L representing the start line of the image. There are four conjectures:

Case 1: when the left effective signals are all 1, compare the first left estimated position and the second left estimated position, and select the smaller one as the left rough estimated position ROUGH_L;

Case 2: when the first and second left effective signals are 1 and 0 respectively, the first left estimated position is taken as the left rough estimated position ROUGH_L;

Situation 3: when the first and second left effective signals are 0 and 1 respectively, use the second left effective signal as the roughly left position ROUGH_L;

Situation 4: When both are 0, maintain the original left rough estimation position ROUGH_L.

From the above description, it can be found that the first left effective signal, the second left effective signal, and the left roughly estimated position ROUGH_L are all updated with smaller possible values, because for the left search range, it is desired to obtain The starting line of the image, that is, the one closer to the left side of the screen.

Furthermore, the right search unit 24 processes these characteristic values U, C, and L in a symmetrical manner with the left search unit 23, and it can be deduced by those with ordinary knowledge in the technical field of the present invention, so here I won't go into details.

To sum up, the position and image detection device of the present invention is only assisted by a column buffer 4, and uses the search units 21, 22, 23, 24 to analyze whether the video content is an image, and the confirmation unit 31 , 32, 33, and 34 are verified to make the identification mechanism more rigorous, so the purpose of the present invention can indeed be achieved.

But the above-mentioned ones are only preferred embodiments of the present invention, and should not limit the scope of the present invention with this, that is, all simple equivalent changes and modifications made according to the scope of the claims of the present invention and the contents of the description of the invention, All still belong to the scope covered by the claims of the present invention.

Claims (18)

1. image detection device is applicable to receive the video flowing that comprises at least one picture that each picture comprises multi-column data, and each columns is according to having a plurality of pixels, and each picture presents an image and a cover side, and this image detection device comprises:

Characteristics unit receives these a plurality of pixels in regular turn and thinks that each pixel determines a pixel characteristic value; And

Search engine comprises:

Image Comparator, whether the pixel characteristic value of measurement current pixel belongs to image to judge it; And

The cover side comparator, whether the pixel characteristic value of measurement current pixel belongs to the cover side to judge it;

This search engine is inferred the picture position based on the judgement of this Image Comparator and this cover side comparator.

2. image detection device according to claim 1, wherein, this characteristics unit also defines search area, and it may be the number of image pixel in each group data that this Image Comparator calculates in this search area, to export first estimated position; It may be the number of cover side pixel in each group data that this cover side comparator calculates in this search area, to export second estimated position.

3. image detection device according to claim 1, wherein, this characteristics unit also defines search area, the pixel pointwise along present columns certificate in this search area of this Image Comparator detects, make image judge the pixel of setting up up to detecting one, and export first estimated position based on this establishment position; The pixel pointwise along present columns certificate in this search area of this cover side comparator detects, and makes the cover side judge the pixel of setting up up to detecting one, and exports second estimated position based on this establishment position.

4. image detection device according to claim 1 is applicable to receive maximum cover side value and minimum cover side value, and wherein, in the characteristic value of current pixel did not fall within the scope that these cover side values are defined, then this Image Comparator judgement current pixel belonged to image.

5. image detection device according to claim 1, be applicable to and receive similar difference and totally different difference, wherein, when current pixel to same group in the characteristic value gap of neighbor less than this similar difference, and when the characteristic value gap of the pixel of same position was greater than this totally different difference in current pixel and the adjacent set, this cover side comparator inferred that current pixel belongs to the cover side.

6. image detection device according to claim 2, wherein, this Image Comparator is optionally to export this first estimated position, this cover side comparator is optionally to export this second estimated position, and this search engine also comprises determining device, as long as this determining device receives this first estimated position, just it is considered as the rough estimate position; And, be that this rough estimate position is used as in this second estimated position when this determining device receives only this second estimated position.

7. image detection device according to claim 3, wherein, this Image Comparator is also exported first useful signal, this cover side comparator is also exported second useful signal, and this search engine also comprises determining device, be when effective when these useful signals show these estimated positions, choose wherein and be used as this rough estimate position near this picture side person; When only wherein a useful signal show when effective, choose corresponding estimated position and be used as this rough estimate position.

8. image detection device according to claim 1 also comprises validator, when the picture position that this search engine is inferred is different from an accurate location, this is inferred the value metering again of picture position; Be worth continuous frequency of occurrence greater than tentative metering critical value up to this, just be used as this accurate location after the renewal with this supposition picture position.

9. image detection device according to claim 1, wherein, this characteristics unit is divided into a luminance component and two chroma components with each pixel, and the respective pixel characteristic value is set at the twice luminance component and these chroma components add the General Logistics Department again divided by four.

10. an image detecting method is applicable to the video flowing that comprises at least one picture, and each picture comprises multi-column data, and each columns is according to having a plurality of pixels, and each picture presents an image and a cover side, and this image detecting method comprises following steps:

For in these a plurality of pixels each determines a pixel characteristic value;

Weigh the pixel characteristic value of current pixel, whether belong to image to judge it;

Weigh the pixel characteristic value of current pixel, whether belong to the cover side to judge it; And

Infer the picture position according to judged result.

11. image detecting method according to claim 10, also comprising a step is the definition search area, wherein, infers that the step of picture position comprises following substep:

Calculating in this search area may be the number of image pixel in each group data, to export first estimated position; And

Calculating in this search area may be the number of cover side pixel in each group data, to export second estimated position.

12. image detecting method according to claim 10, also comprising a step is the definition search area, wherein, infers that the step of picture position comprises following substep:

Pixel pointwise along present columns certificate in this search area detects, and makes image judge the pixel of setting up up to detecting one, and exports first estimated position based on this establishment position; And

Pixel pointwise along present columns certificate in this search area detects, and makes the cover side judge the pixel of setting up up to detecting one, and exports second estimated position based on this establishment position.

13. image detecting method according to claim 10 wherein, judges that characteristic value that step that current pixel belongs to image is based on current pixel does not fall within the scope that maximum cover side value and minimum cover side value defined.

14. image detecting method according to claim 10, wherein, judge step that current pixel belongs to the cover side be based on current pixel with same group in the characteristic value gap of neighbor less than this similar difference, and the characteristic value gap of the pixel of current pixel and the interior same position of adjacent set is greater than this totally different difference.

15. image detecting method according to claim 11 wherein, is optionally to export this first estimated position and this second estimated position, and infers that the step of picture position also comprises following substep:

As long as receive this first estimated position, just it is considered as a rough estimate position; And

When receiving only this second estimated position, be that this rough estimate position is used as in this second estimated position.

16. image detecting method according to claim 12 wherein, infers that the step of picture position also comprises following substep:

Output is relevant to first useful signal of this first estimated position;

Output is relevant to second useful signal of this second estimated position;

Be when effective when these useful signals show these estimated positions, choose wherein and be used as this rough estimate position near this picture side person;

When only wherein a useful signal show when effective, choose corresponding estimated position and be used as this rough estimate position.

17. image detecting method according to claim 10 wherein, also comprises following steps:

When the picture position of being inferred is different from an accurate location, this is inferred the value metering again of picture position; And

Be worth continuous frequency of occurrence greater than tentative metering critical value up to this, just be used as this accurate location after the renewal with this supposition picture position.

18. image detecting method according to claim 10 wherein, determines the step of this pixel characteristic value to comprise following substep:

Each pixel is divided into a luminance component and two chroma components; And

The respective pixel characteristic value is set at the twice luminance component and these chroma components add the General Logistics Department again divided by four.

Images