45 results about "Texture coding" patented technology

Methods of adaptive transform type based on transform unit (TU) size for enhancement layer (EL) coding and multiple motion candidates for EL coding based on corresponding base layer (BL) video data are provided. One method selects a transform type from multiple allowable transform types based on the TU size and applies the selected transform type to the transform units of the inter-layer prediction processed data. Another method derives multiple motion candidates for the EL video data coded in Merge mode or Inter mode based on motion information associated with the corresponding BL video data.

A motion estimation method using adaptive mode decision is disclosed. The method includes a motion vector difference value calculation step of calculating a motion vector difference value using an input motion vector estimation value x component for a current block and an input x offset corresponding to a current SAD. At the MVD Variable Length Coding (VLC) step, the length of a bit string, which is obtained by performing variable-length coding on an MVDx, is calculated. At a motion vector difference value calculation step, a motion vector difference value is calculated using an input motion vector estimation value y component for a current block and an input y offset corresponding to the current SAD. At an MVD VLC step, the length of a bit string, which is obtained by performing variable-length coding on an MVDy, is calculated. Thereafter, the amount of motion vector coding is produced by adding the MVDx and the MVDy. The amount of texture coding of a current block or a macro block is estimated using SAD values and quantization coefficients of previous macro blocks. A SAD correction coefficient is produced using the amount of motion vector coding and the texture vector coding amount. Finally, the SAD values are multiplied by the SAD correction coefficient, thus correcting the SAD values.

Methods of adaptive transform type based on transform unit (TU) size for enhancement layer (EL) coding and multiple motion candidates for EL coding based on corresponding base layer (BL) video data are provided. One method selects a transform type from multiple allowable transform types based on the TU size and applies the selected transform type to the transform units of the inter-layer prediction processed data. Another method derives multiple motion candidates for the EL video data coded in Merge mode or Inter mode based on motion information associated with the corresponding BL video data.

The invention discloses a three-dimensional reconstruction method based on texture-coded images, which includes: step 1, projecting a color-coded image generated by M-array coding onto an object to be measured, and using a camera to photograph the region to be measured to obtain left and right images. In step 2, the target area is extracted based on the Hough circle detection method and the principle of perspective transformation, so as to avoid the influence of environmental debris on the projection area. Step 3, image enhancement based on color migration technology and color recognition preprocessing, converting the color information of the image into code values. Step 4, direct decoding for M-array encoding method to obtain matching point pairs. Step 5, using the obtained point pairs with the same name, perform 3D reconstruction based on the principle of stereo vision, and obtain the 3D coordinates of the spatial points corresponding to the 2D points. The present invention combines spatial codec and binocular vision structured light three-dimensional reconstruction technology to improve the speed and accuracy of three-dimensional reconstruction, and provides a new idea for high-efficiency three-dimensional reconstruction under the premise of maintaining a high degree of simulation.

The invention provides a hand vein recognition method based on the fusion of structure coding characteristics and texture coding characteristics, belonging to the technical field of intelligent monitoring in computer vision. The method comprises the following steps of: step 1, acquiring and preprocessing an image; step 2, extracting the structure coding characteristics; step 3, extracting the hand vein texture coding characteristics; step 4, fusing the structure coding characteristics with the hand vein texture coding characteristics; and step 5, performing recognition through a sorter, thereby obtaining a result. The invention provides the hand vein recognition method based on the fusion of the structure coding characteristics and the texture coding characteristics, wherein binary codingis performed on the extracted structure characteristics and texture characteristics, which is advantageous for the retention of information in the characteristic fusion; the result obtained by fusingthe characteristics is far better than the result of recognition obtained by only employing the structure coding characteristics and the result of recognition obtained by only employing the texture coding characteristics; and the robustness for image distortion and wrong segmentation is high, therefore, the hand vein can be correctly recognized in the presence of certain image distortion and wrong segmentation.